CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: FMR1 gene</title> <meta name="description" content="Search results for: FMR1 gene"> <meta name="keywords" content="FMR1 gene"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="FMR1 gene" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="FMR1 gene"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1508</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: FMR1 gene</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1508</span> FMR1 Gene Carrier Screening for Premature Ovarian Insufficiency in Females: An Indian Scenario</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sarita%20Agarwal">Sarita Agarwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Deepika%20Delsa%20Dean"> Deepika Delsa Dean</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genetic%20counseling" title="genetic counseling">genetic counseling</a>, <a href="https://publications.waset.org/abstracts/search?q=FMR1%20gene" title=" FMR1 gene"> FMR1 gene</a>, <a href="https://publications.waset.org/abstracts/search?q=fragile%20x-associated%20primary%20ovarian%20insufficiency" title=" fragile x-associated primary ovarian insufficiency"> fragile x-associated primary ovarian insufficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=premutation" title=" premutation"> premutation</a> </p> <a href="https://publications.waset.org/abstracts/118798/fmr1-gene-carrier-screening-for-premature-ovarian-insufficiency-in-females-an-indian-scenario" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/118798.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1507</span> Global Developmental Delay and Its Association with Risk Factors: Validation by Structural Equation Modelling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bavneet%20Kaur%20Sidhu">Bavneet Kaur Sidhu</a>, <a href="https://publications.waset.org/abstracts/search?q=Manoj%20Tiwari"> Manoj Tiwari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Global Developmental Delay (GDD) is a common pediatric condition. Etiologies of GDD might, however, differ in developing countries. In the last decade, sporadic families are being reported in various countries. As to the author’s best knowledge, many risk factors and their correlation with the prevalence of GDD have been studied but its statistical correlation has not been done. Thus we propose the present study by targeting the risk factor, prevalence and their statistical correlation with GDD. FMR1 gene was studied to confirm the disease and its penetrance. A complete questionnaire-based performance was designed for the statistical studies having a personal, past and present medical history along with their socio-economic status as well. Methods: We distributed the children’s age in 4 different age groups having 5-year intervals and applied structural equation modeling (SEM) techniques, Spearman’s rank correlation coefficient, Karl Pearson correlation coefficient, and chi-square test.Result: A total of 1100 families were enrolled for this study; among them, 330 were clinically and biologically confirmed (radiological studies) for the disease, 204 were males (61.8%), 126 were females (38.18%). We found that 27.87% were genetic and 72.12 were sporadic, out of 72.12 %, 43.277% cases from urban and 56.72% from the rural locality, the mothers' literacy rate was 32.12% and working women numbers were 41.21%. Conclusions: There is a significant association between mothers' age and GDD prevalence, which is also followed by mothers' literacy rate and mothers' occupation, whereas there was no association between fathers' age and GDD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20developmental%20delay" title="global developmental delay">global developmental delay</a>, <a href="https://publications.waset.org/abstracts/search?q=FMR1%20gene" title=" FMR1 gene"> FMR1 gene</a>, <a href="https://publications.waset.org/abstracts/search?q=spearman%E2%80%99%20rank%20correlation%20coefficient" title=" spearman’ rank correlation coefficient"> spearman’ rank correlation coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20equation%20modeling" title=" structural equation modeling"> structural equation modeling</a> </p> <a href="https://publications.waset.org/abstracts/113873/global-developmental-delay-and-its-association-with-risk-factors-validation-by-structural-equation-modelling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/113873.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">135</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1506</span> Intelligent CRISPR Design for Bone Regeneration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yu-Chen%20Hu">Yu-Chen Hu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Gene editing by CRISPR and gene regulation by microRNA or CRISPR activation have dramatically changed the way to manipulate cellular gene expression and cell fate. In recent years, various gene editing and gene manipulation technologies have been applied to control stem cell differentiation to enhance tissue regeneration. This research will focus on how to develop CRISPR, CRISPR activation (CRISPRa), CRISPR inhibition (CRISPRi), as well as bi-directional CRISPR-AI gene regulation technologies to control cell differentiation and bone regeneration. Moreover, in this study, CRISPR/Cas13d-mediated RNA editng for miRNA editing and bone regeneration will be discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gene%20therapy" title="gene therapy">gene therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=bone%20regeneration" title=" bone regeneration"> bone regeneration</a>, <a href="https://publications.waset.org/abstracts/search?q=stem%20cell" title=" stem cell"> stem cell</a>, <a href="https://publications.waset.org/abstracts/search?q=CRISPR" title=" CRISPR"> CRISPR</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20regulation" title=" gene regulation"> gene regulation</a> </p> <a href="https://publications.waset.org/abstracts/168750/intelligent-crispr-design-for-bone-regeneration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168750.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">90</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1505</span> Construction of the Large Scale Biological Networks from Microarrays</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fadhl%20Alakwaa">Fadhl Alakwaa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the sustainable goals of the system biology is understanding gene-gene interactions. Hence, gene regulatory networks (GRN) need to be constructed for understanding the disease ontology and to reduce the cost of drug development. To construct gene regulatory from gene expression we need to overcome many challenges such as data denoising and dimensionality. In this paper, we develop an integrated system to reduce data dimension and remove the noise. The generated network from our system was validated via available interaction databases and was compared to previous methods. The result revealed the performance of our proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gene%20regulatory%20network" title="gene regulatory network">gene regulatory network</a>, <a href="https://publications.waset.org/abstracts/search?q=biclustering" title=" biclustering"> biclustering</a>, <a href="https://publications.waset.org/abstracts/search?q=denoising" title=" denoising"> denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=system%20biology" title=" system biology"> system biology</a> </p> <a href="https://publications.waset.org/abstracts/74607/construction-of-the-large-scale-biological-networks-from-microarrays" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74607.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">239</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1504</span> Identification of Mx Gene Polymorphism in Indragiri Hulu duck by PCR-RFLP</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Restu%20Misrianti">Restu Misrianti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The amino acid variation of Asn (allele A) at position 631 in Mx gene was specific to positive antiviral to avian viral desease. This research was aimed at identifying polymorphism of Mx gene in duck using molecular technique. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) technique was used to select the genotype of AA, AG and GG. There were thirteen duck from Indragiri Hulu regency (Riau Province) used in this experiment. DNA amplification results showed that the Mx gene in duck is found in a 73 bp fragment. Mx gene in duck did not show any polymorphism. The frequency of the resistant allele (AA) was 0%, while the frequency of the susceptible allele (GG) was 100%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=duck" title="duck">duck</a>, <a href="https://publications.waset.org/abstracts/search?q=Mx%20gene" title=" Mx gene"> Mx gene</a>, <a href="https://publications.waset.org/abstracts/search?q=PCR" title=" PCR"> PCR</a>, <a href="https://publications.waset.org/abstracts/search?q=RFLP" title=" RFLP"> RFLP</a> </p> <a href="https://publications.waset.org/abstracts/37764/identification-of-mx-gene-polymorphism-in-indragiri-hulu-duck-by-pcr-rflp" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37764.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">324</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1503</span> Macronutrients and the FTO Gene Expression in Hypothalamus: A Systematic Review of Experimental Studies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeid%20Doaei">Saeid Doaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The various studies have examined the relationship between FTO gene expression and macronutrients levels. In order to obtain better viewpoint from this interactions, all of the existing studies were reviewed systematically. All published papers have been obtained and reviewed using standard and sensitive keywords from databases such as CINAHL, Embase, PubMed, PsycInfo, and the Cochrane, from 1990 to 2016. The results indicated that all of 6 studies that met the inclusion criteria (from a total of 428 published article) found FTO gene expression changes at short-term follow-ups. Four of six studies found an increased FTO gene expression after calorie restriction, while two of them indicated decreased FTO gene expression. The effect of protein, carbohydrate and fat were separately assessed and suggested by all of six studies. In conclusion, the level of FTO gene expression in hypothalamus is related to macronutrients levels. Future research should evaluate the long-term impact of dietary interventions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=obesity" title="obesity">obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression" title=" gene expression"> gene expression</a>, <a href="https://publications.waset.org/abstracts/search?q=FTO" title=" FTO"> FTO</a>, <a href="https://publications.waset.org/abstracts/search?q=macronutrients" title=" macronutrients"> macronutrients</a> </p> <a href="https://publications.waset.org/abstracts/71018/macronutrients-and-the-fto-gene-expression-in-hypothalamus-a-systematic-review-of-experimental-studies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71018.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">267</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1502</span> Integration of Microarray Data into a Genome-Scale Metabolic Model to Study Flux Distribution after Gene Knockout</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mona%20Heydari">Mona Heydari</a>, <a href="https://publications.waset.org/abstracts/search?q=Ehsan%20Motamedian"> Ehsan Motamedian</a>, <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Abbas%20Shojaosadati"> Seyed Abbas Shojaosadati</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metabolic%20network" title="metabolic network">metabolic network</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20knockout" title=" gene knockout"> gene knockout</a>, <a href="https://publications.waset.org/abstracts/search?q=flux%20balance%20analysis" title=" flux balance analysis"> flux balance analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray%20data" title=" microarray data"> microarray data</a>, <a href="https://publications.waset.org/abstracts/search?q=integration" title=" integration"> integration</a> </p> <a href="https://publications.waset.org/abstracts/15750/integration-of-microarray-data-into-a-genome-scale-metabolic-model-to-study-flux-distribution-after-gene-knockout" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15750.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">579</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1501</span> Finding Bicluster on Gene Expression Data of Lymphoma Based on Singular Value Decomposition and Hierarchical Clustering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alhadi%20Bustaman">Alhadi Bustaman</a>, <a href="https://publications.waset.org/abstracts/search?q=Soeganda%20Formalidin"> Soeganda Formalidin</a>, <a href="https://publications.waset.org/abstracts/search?q=Titin%20Siswantining"> Titin Siswantining</a> </p> <p class="card-text"><strong>Abstract:</strong></p> DNA microarray technology is used to analyze thousand gene expression data simultaneously and a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been used for analyzing gene expression data. However, when analyzing very large and heterogeneous collections of gene expression data, conventional clustering methods often cannot produce a satisfactory solution. Biclustering algorithm has been used as an alternative approach to identifying structures from gene expression data. In this paper, we introduce a transform technique based on singular value decomposition to identify normalized matrix of gene expression data followed by Mixed-Clustering algorithm and the Lift algorithm, inspired in the node-deletion and node-addition phases proposed by Cheng and Church based on Agglomerative Hierarchical Clustering (AHC). Experimental study on standard datasets demonstrated the effectiveness of the algorithm in gene expression data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=agglomerative%20hierarchical%20clustering%20%28AHC%29" title="agglomerative hierarchical clustering (AHC)">agglomerative hierarchical clustering (AHC)</a>, <a href="https://publications.waset.org/abstracts/search?q=biclustering" title=" biclustering"> biclustering</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression%20data" title=" gene expression data"> gene expression data</a>, <a href="https://publications.waset.org/abstracts/search?q=lymphoma" title=" lymphoma"> lymphoma</a>, <a href="https://publications.waset.org/abstracts/search?q=singular%20value%20decomposition%20%28SVD%29" title=" singular value decomposition (SVD)"> singular value decomposition (SVD)</a> </p> <a href="https://publications.waset.org/abstracts/72889/finding-bicluster-on-gene-expression-data-of-lymphoma-based-on-singular-value-decomposition-and-hierarchical-clustering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72889.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">278</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1500</span> Mutations in MTHFR Gene Associated with Mental Retardation and Cerebral Palsy Combined with Mental Retardation in Erbil City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hazha%20Hidayat">Hazha Hidayat</a>, <a href="https://publications.waset.org/abstracts/search?q=Shayma%20Ibrahim"> Shayma Ibrahim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Folate metabolism plays a crucial role in the normal development of the neonatal central nervous system. It is regulated by MTHFR gene polymorphism. Any factors, which will affect this metabolism either by hereditary or gene mutation will lead to many mental disorders. The purpose of this study was to investigate whether MTHFR gene mutation contributes to the development of mental retardation and CP combined with mental retardation in Erbil city. DNA was isolated from the peripheral blood samples of 40 cases suffering from mental retardation (MR) and CP combined with MR were recruited, sequence the 4, 6, 7, 8 exons of the MTHFR gene were done to identify the variants. Exons were amplified by PCR technique and then sequenced according to Sanger method to show the differences with MTHFR reference sequences. We observed (14) mutations in 4, 6, 7, 8 exons in the MTHFR gene associated with Cerebral Palsy combined with mental retardation included deletion, insertion, Substitution. The current study provides additional evidence that multiple variations in the MTHFR gene are associated with mental retardation and Cerebral Palsy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=methylenetetrahydrofolate%20reductase%20%28MTHFR%29%20gene" title="methylenetetrahydrofolate reductase (MTHFR) gene">methylenetetrahydrofolate reductase (MTHFR) gene</a>, <a href="https://publications.waset.org/abstracts/search?q=SNPs" title=" SNPs"> SNPs</a>, <a href="https://publications.waset.org/abstracts/search?q=homocysteine" title=" homocysteine"> homocysteine</a>, <a href="https://publications.waset.org/abstracts/search?q=sequencing" title=" sequencing"> sequencing</a> </p> <a href="https://publications.waset.org/abstracts/70927/mutations-in-mthfr-gene-associated-with-mental-retardation-and-cerebral-palsy-combined-with-mental-retardation-in-erbil-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70927.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">308</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1499</span> A Review of Effective Gene Selection Methods for Cancer Classification Using Microarray Gene Expression Profile</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hala%20Alshamlan">Hala Alshamlan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ghada%20Badr"> Ghada Badr</a>, <a href="https://publications.waset.org/abstracts/search?q=Yousef%20Alohali"> Yousef Alohali </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gene%20selection" title="gene selection">gene selection</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer%20classification" title=" cancer classification"> cancer classification</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray" title=" microarray"> microarray</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression%20profile" title=" gene expression profile"> gene expression profile</a> </p> <a href="https://publications.waset.org/abstracts/8991/a-review-of-effective-gene-selection-methods-for-cancer-classification-using-microarray-gene-expression-profile" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8991.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">454</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1498</span> An Integrated Visualization Tool for Heat Map and Gene Ontology Graph</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Somyung%20Oh">Somyung Oh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeonghyeon%20Ha"> Jeonghyeon Ha</a>, <a href="https://publications.waset.org/abstracts/search?q=Kyungwon%20Lee"> Kyungwon Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sejong%20Oh"> Sejong Oh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Microarray is a general scheme to find differentially expressed genes for target concept. The output is expressed by heat map, and biologists analyze related terms of gene ontology to find some characteristics of differentially expressed genes. In this paper, we propose integrated visualization tool for heat map and gene ontology graph. Previous two methods are used by static manner and separated way. Proposed visualization tool integrates them and users can interactively manage it. Users may easily find and confirm related terms of gene ontology for given differentially expressed genes. Proposed tool also visualize connections between genes on heat map and gene ontology graph. We expect biologists to find new meaningful topics by proposed tool. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heat%20map" title="heat map">heat map</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20ontology" title=" gene ontology"> gene ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray" title=" microarray"> microarray</a>, <a href="https://publications.waset.org/abstracts/search?q=differentially%20expressed%20gene" title=" differentially expressed gene"> differentially expressed gene</a> </p> <a href="https://publications.waset.org/abstracts/49151/an-integrated-visualization-tool-for-heat-map-and-gene-ontology-graph" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49151.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">316</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1497</span> Application of KL Divergence for Estimation of Each Metabolic Pathway Genes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shohei%20Maruyama">Shohei Maruyama</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasuo%20Matsuyama"> Yasuo Matsuyama</a>, <a href="https://publications.waset.org/abstracts/search?q=Sachiyo%20Aburatani"> Sachiyo Aburatani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metabolic%20pathways" title="metabolic pathways">metabolic pathways</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression%20data" title=" gene expression data"> gene expression data</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray" title=" microarray"> microarray</a>, <a href="https://publications.waset.org/abstracts/search?q=Kullback%E2%80%93Leibler%20divergence" title=" Kullback–Leibler divergence"> Kullback–Leibler divergence</a>, <a href="https://publications.waset.org/abstracts/search?q=KL%20divergence" title=" KL divergence"> KL divergence</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machines" title=" support vector machines"> support vector machines</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a> </p> <a href="https://publications.waset.org/abstracts/23964/application-of-kl-divergence-for-estimation-of-each-metabolic-pathway-genes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23964.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">403</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1496</span> The Use of Medical Biotechnology to Treat Genetic Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rachel%20Matar">Rachel Matar</a>, <a href="https://publications.waset.org/abstracts/search?q=Maxime%20Merheb"> Maxime Merheb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Chemical drugs have been used for many centuries as the only way to cure diseases until the novel gene therapy has been created in 1960. Gene therapy is based on the insertion, correction, or inactivation of genes to treat people with genetic illness (1). Gene therapy has made wonders in Parkison’s, Alzheimer and multiple sclerosis. In addition to great promises in the healing of deadly diseases like many types of cancer and autoimmune diseases (2). This method implies the use of recombinant DNA technology with the help of different viral and non-viral vectors (3). It is nowadays used in somatic cells as well as embryos and gametes. Beside all the benefits of gene therapy, this technique is deemed by some opponents as an ethically unacceptable treatment as it implies playing with the genes of living organisms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gene%20therapy" title="gene therapy">gene therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20disease" title=" genetic disease"> genetic disease</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer" title=" cancer"> cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20sclerosis" title=" multiple sclerosis"> multiple sclerosis</a> </p> <a href="https://publications.waset.org/abstracts/46593/the-use-of-medical-biotechnology-to-treat-genetic-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46593.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">541</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1495</span> PRKAG3 and RYR1 Gene in Latvian White Pigs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Daina%20Jonkus">Daina Jonkus</a>, <a href="https://publications.waset.org/abstracts/search?q=Liga%20Paura"> Liga Paura</a>, <a href="https://publications.waset.org/abstracts/search?q=Tatjana%20Sjakste"> Tatjana Sjakste</a>, <a href="https://publications.waset.org/abstracts/search?q=Kristina%20Dokane"> Kristina Dokane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study was to analyse PRKAG3 and RYR1 gene and genotypes frequencies in Latvian White pigs’ breed. Genotypes of RYR1 gene two loci (rs196953058 and rs323041392) in 89 exon and PRKAG3 gene two loci (rs196958025 and rs344045190) in gene promoter were detected in 103 individuals of Latvian white pigs’ breed. Analysis of RYR1 gene loci rs196953058 shows all individuals are homozygous by T allele and all animals are with genotypes TT, its mean - in 2769 position is Phenylalanine. Analysis of RYR1 gene loci rs323041392 shows all individuals are homozygous by G allele and all animals are with genotypes GG, its mean - in 4119 positions is Asparagine. In loci rs196953058 and rs323041392, there were no gene polymorphisms. All analysed individuals by two loci rs196953058-rs323041392 have TT-GG genotypes or Phe-Asp amino acids. In PRKAG3 gene loci rs196958025 and rs344045190 there was gene polymorphisms. In both loci frequencies for A allele was higher: 84.6% for rs196958025 and 73.0% for rs344045190. Analysis of PRKAG3 gene loci rs196958025 shows 74% of individuals are homozygous by An allele and animals are with genotypes AA. Only 4% of individuals are homozygous by G allele and animals are with genotypes GG, which is associated with pale meat colour and higher drip loss. Analysis of PRKAG3 gene loci rs344045190 shows 46% of individuals are homozygous with genotypes AA and 54% of individuals are heterozygous with genotypes AG. There are no individuals with GG genotypes. According to the results, in Latvian white pigs population there are no rs344435545 (RYR1 gene) CT heterozygous or TT recessive homozygous genotypes, which is related to the meat quality and pigs’ stress syndrome; and there are 4% rs196958025 (PRKAG3 gene) GG recessive homozygote genotypes, which is related to the meat quality. Acknowledgment: the investigation is supported by VPP 2014-2017 AgroBioRes Project No. 3 LIVESTOCK. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genotype%20frequencies" title="genotype frequencies">genotype frequencies</a>, <a href="https://publications.waset.org/abstracts/search?q=pig" title=" pig"> pig</a>, <a href="https://publications.waset.org/abstracts/search?q=PRKAG3" title=" PRKAG3"> PRKAG3</a>, <a href="https://publications.waset.org/abstracts/search?q=RYR1" title=" RYR1"> RYR1</a> </p> <a href="https://publications.waset.org/abstracts/59238/prkag3-and-ryr1-gene-in-latvian-white-pigs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59238.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">210</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1494</span> Bioinformatic Study of Follicle Stimulating Hormone Receptor (FSHR) Gene in Different Buffalo Breeds</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Mustafa">Hamid Mustafa</a>, <a href="https://publications.waset.org/abstracts/search?q=Adeela%20Ajmal"> Adeela Ajmal</a>, <a href="https://publications.waset.org/abstracts/search?q=Kim%20EuiSoo"> Kim EuiSoo</a>, <a href="https://publications.waset.org/abstracts/search?q=Noor-ul-Ain"> Noor-ul-Ain</a> </p> <p class="card-text"><strong>Abstract:</strong></p> World wild, buffalo production is considered as most important component of food industry. Efficient buffalo production is related with reproductive performance of this species. Lack of knowledge of reproductive efficiency and its related genes in buffalo species is a major constraint for sustainable buffalo production. In this study, we performed some bioinformatics analysis on Follicle Stimulating Hormone Receptor (FSHR) gene and explored the possible relationship of this gene among different buffalo breeds and with other farm animals. We also found the evolution pattern for this gene among these species. We investigate CDS lengths, Stop codon variation, homology search, signal peptide, isoelectic point, tertiary structure, motifs and phylogenetic tree. The results of this study indicate 4 different motif in this gene, which are Activin-recp, GS motif, STYKc Protein kinase and transmembrane. The results also indicate that this gene has very close relationship with cattle, bison, sheep and goat. Multiple alignment (MA) showed high conservation of motif which indicates constancy of this gene during evolution. The results of this study can be used and applied for better understanding of this gene for better characterization of Follicle Stimulating Hormone Receptor (FSHR) gene structure in different farm animals, which would be helpful for efficient breeding plans for animal’s production. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=buffalo" title="buffalo">buffalo</a>, <a href="https://publications.waset.org/abstracts/search?q=FSHR%20gene" title=" FSHR gene"> FSHR gene</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a>, <a href="https://publications.waset.org/abstracts/search?q=production" title=" production "> production </a> </p> <a href="https://publications.waset.org/abstracts/22070/bioinformatic-study-of-follicle-stimulating-hormone-receptor-fshr-gene-in-different-buffalo-breeds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22070.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">532</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1493</span> Polymorphism of Candidate Genes for Meat Production in Lori Sheep </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shahram%20Nanekarania">Shahram Nanekarania</a>, <a href="https://publications.waset.org/abstracts/search?q=Majid%20Goodarzia"> Majid Goodarzia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Calpastatin and callipyge have been known as one of the candidate genes in meat quality and quantity. Calpastatin gene has been located to chromosome 5 of sheep and callipyge gene has been localized in the telomeric region on ovine chromosome 18. The objective of this study was identification of calpastatin and callipyge genes polymorphism and analysis of genotype structure in population of Lori sheep kept in Iran. Blood samples were taken from 120 Lori sheep breed and genomic DNA was extracted by salting out method. Polymorphism was identified using the PCR-RFLP technique. The PCR products were digested with MspI and FaqI restriction enzymes for calpastatin gene and callipyge gene, respectively. In this population, three patterns were observed and AA, AB, BB genotype have been identified with the 0.32, 0.63, 0.05 frequencies for calpastatin gene. The results obtained for the callipyge gene revealed that only the wild-type allele A was observed, indicating that only genotype AA was present in the population under consideration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=polymorphism" title="polymorphism">polymorphism</a>, <a href="https://publications.waset.org/abstracts/search?q=calpastatin" title=" calpastatin"> calpastatin</a>, <a href="https://publications.waset.org/abstracts/search?q=callipyge" title=" callipyge"> callipyge</a>, <a href="https://publications.waset.org/abstracts/search?q=PCR-RFLP" title=" PCR-RFLP"> PCR-RFLP</a>, <a href="https://publications.waset.org/abstracts/search?q=Lori%20sheep" title=" Lori sheep"> Lori sheep</a> </p> <a href="https://publications.waset.org/abstracts/8594/polymorphism-of-candidate-genes-for-meat-production-in-lori-sheep" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8594.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">611</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1492</span> Gene Names Identity Recognition Using Siamese Network for Biomedical Publications</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Micheal%20Olaolu%20Arowolo">Micheal Olaolu Arowolo</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Azam"> Muhammad Azam</a>, <a href="https://publications.waset.org/abstracts/search?q=Fei%20He"> Fei He</a>, <a href="https://publications.waset.org/abstracts/search?q=Mihail%20Popescu"> Mihail Popescu</a>, <a href="https://publications.waset.org/abstracts/search?q=Dong%20Xu"> Dong Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biological%20pathway" title="biological pathway">biological pathway</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20identification" title=" gene identification"> gene identification</a>, <a href="https://publications.waset.org/abstracts/search?q=object%20detection" title=" object detection"> object detection</a>, <a href="https://publications.waset.org/abstracts/search?q=Siamese%20network" title=" Siamese network"> Siamese network</a> </p> <a href="https://publications.waset.org/abstracts/160725/gene-names-identity-recognition-using-siamese-network-for-biomedical-publications" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160725.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">292</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1491</span> Using Gene Expression Programming in Learning Process of Rough Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanaa%20Rashed%20Abdallah">Sanaa Rashed Abdallah</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasser%20F.%20Hassan"> Yasser F. Hassan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rough%20sets" title="rough sets">rough sets</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression%20programming" title=" gene expression programming"> gene expression programming</a>, <a href="https://publications.waset.org/abstracts/search?q=rough%20neural%20networks" title=" rough neural networks"> rough neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/41805/using-gene-expression-programming-in-learning-process-of-rough-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41805.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">383</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1490</span> Human Papillomavirus Type 16 E4 Gene Variation as Risk Factor for Cervical Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yudi%20Zhao">Yudi Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Ziyun%20Zhou"> Ziyun Zhou</a>, <a href="https://publications.waset.org/abstracts/search?q=Yueting%20Yao"> Yueting Yao</a>, <a href="https://publications.waset.org/abstracts/search?q=Shuying%20Dai"> Shuying Dai</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhiling%20Yan"> Zhiling Yan</a>, <a href="https://publications.waset.org/abstracts/search?q=Longyu%20Yang"> Longyu Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuanyin%20Li"> Chuanyin Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Shi"> Li Shi</a>, <a href="https://publications.waset.org/abstracts/search?q=Yufeng%20Yao"> Yufeng Yao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> HPV16 E4 gene plays an important role in viral genome amplification and release. Therefore, a variation of the E4 gene nucleic acid sequence may affect the carcinogenicity of HPV16. In order to understand the relationship between the variation of HPV16 E4 gene and cervical cancer, this study was to amplify and sequence the DNA sequences of E4 genes in 118 HPV16-positive cervical cancer patients and 151 HPV16-positive asymptomatic individuals. After obtaining E4 gene sequences, the phylogenetic trees were constructed by the Neighbor-joining method for gene variation analysis. The results showed that: 1) The distribution of HPV16 variants between the case group and the control group differed greatly (P = 0.015)，and the Asian-American（AA）variant was likely to relate to the occurrence of cervical cancer. 2) DNA sequence analysis showed that there were significant differences in the distribution of 8 variants between the case group and the control group (P < 0.05). And 3) In European (EUR) variant, two variations, C3384T (L18L) and A3449G (P39P), were associated with the initiation and development of cervical cancer. The results suggested that the variation of HPV16 E4 gene may be a contributor affecting the occurrence as well as the development of cervical cancer, and different HPV16 variants may have different carcinogenic capability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cervical%20cancer" title="cervical cancer">cervical cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=HPV16" title=" HPV16"> HPV16</a>, <a href="https://publications.waset.org/abstracts/search?q=E4%20gene" title=" E4 gene"> E4 gene</a>, <a href="https://publications.waset.org/abstracts/search?q=variations" title=" variations"> variations</a> </p> <a href="https://publications.waset.org/abstracts/110019/human-papillomavirus-type-16-e4-gene-variation-as-risk-factor-for-cervical-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110019.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">171</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1489</span> Analysis of OPG Gene Polymorphism T245G (rs3134069) in Slovak Postmenopausal Women</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=I.%20Boro%C5%88ov%C3%A1">I. Boroňová</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Bernasovsk%C3%A1"> J. Bernasovská</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20K%C4%BEoc"> J. Kľoc</a>, <a href="https://publications.waset.org/abstracts/search?q=Z.%20Tomkov%C3%A1"> Z. Tomková</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Petrej%C4%8D%C3%ADkov%C3%A1"> E. Petrejčíková</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Ma%C4%8Dekov%C3%A1"> S. Mačeková</a>, <a href="https://publications.waset.org/abstracts/search?q=J.%20Por%C3%A1%C4%8Dov%C3%A1"> J. Poráčová</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20M.%20Bla%C5%A1%C4%8D%C3%A1kov%C3%A1"> M. M. Blaščáková</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Osteoporosis is a common multifactorial disease with a strong genetic component characterized by reduced bone mass and increased risk of fractures. Genetic factors play an important role in the pathogenesis of osteoporosis. The aim of our study was to identify the genotype and allele distribution of T245G polymorphism in OPG gene in Slovak postmenopausal women. A total of 200 unrelated Slovak postmenopausal women with diagnosed osteoporosis and 200 normal controls were genotyped for T245G (rs3134069) polymorphism of OPG gene. Genotyping was performed using the Custom Taqman®SNP Genotyping assays. Genotypes and alleles frequencies showed no significant differences (p=0.5551; p=0.6022). The results of the present study confirm the importance of T245G polymorphism in OPG gene in the pathogenesis of osteoporosis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OPG%20gene" title="OPG gene">OPG gene</a>, <a href="https://publications.waset.org/abstracts/search?q=T245G%20polymorphism" title=" T245G polymorphism"> T245G polymorphism</a>, <a href="https://publications.waset.org/abstracts/search?q=osteoporosis" title=" osteoporosis"> osteoporosis</a>, <a href="https://publications.waset.org/abstracts/search?q=T245G%20polymorphism" title=" T245G polymorphism"> T245G polymorphism</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20PCR" title=" real-time PCR "> real-time PCR </a> </p> <a href="https://publications.waset.org/abstracts/12859/analysis-of-opg-gene-polymorphism-t245g-rs3134069-in-slovak-postmenopausal-women" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12859.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">409</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1488</span> Construction of a Fusion Gene Carrying E10A and K5 with 2A Peptide-Linked by Using Overlap Extension PCR</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tiancheng%20Lan">Tiancheng Lan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> E10A is a kind of replication-defective adenovirus which carries the human endostatin gene to inhibit the growth of tumors. Kringle 5(K5) has almost the same function as angiostatin to also inhibit the growth of tumors since they are all the byproduct of the proteolytic cleavage of plasminogen. Tumor size increasing can be suppressed because both of the endostatin and K5 can restrain the angiogenesis process. Therefore, in order to improve the treatment effect on tumor, 2A peptide is used to construct a fusion gene carrying both E10A and K5. Using 2A peptide is an ideal strategy when a fusion gene is expressed because it can avoid many problems during the expression of more than one kind of protein. The overlap extension PCR is also used to connect 2A peptide with E10A and K5. The final construction of fusion gene E10A-2A-K5 can provide a possible new method of the anti-angiogenesis treatment with a better expression performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=E10A" title="E10A">E10A</a>, <a href="https://publications.waset.org/abstracts/search?q=Kringle%205" title=" Kringle 5"> Kringle 5</a>, <a href="https://publications.waset.org/abstracts/search?q=2A%20peptide" title=" 2A peptide"> 2A peptide</a>, <a href="https://publications.waset.org/abstracts/search?q=overlap%20extension%20PCR" title=" overlap extension PCR"> overlap extension PCR</a> </p> <a href="https://publications.waset.org/abstracts/132643/construction-of-a-fusion-gene-carrying-e10a-and-k5-with-2a-peptide-linked-by-using-overlap-extension-pcr" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132643.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1487</span> SCANet: A Workflow for Single-Cell Co-Expression Based Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mhaned%20Oubounyt">Mhaned Oubounyt</a>, <a href="https://publications.waset.org/abstracts/search?q=Jan%20Baumbach"> Jan Baumbach</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=single-cell" title="single-cell">single-cell</a>, <a href="https://publications.waset.org/abstracts/search?q=co-expression%20networks" title=" co-expression networks"> co-expression networks</a>, <a href="https://publications.waset.org/abstracts/search?q=drug-gene%20interactions" title=" drug-gene interactions"> drug-gene interactions</a>, <a href="https://publications.waset.org/abstracts/search?q=co-regulatory%20networks" title=" co-regulatory networks"> co-regulatory networks</a> </p> <a href="https://publications.waset.org/abstracts/161853/scanet-a-workflow-for-single-cell-co-expression-based-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161853.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1486</span> A C/T Polymorphism at the 5’ Untranslated Region of CD40 Gene in Patients Associated with Graves’ Disease in Kumaon Region</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanjeev%20Kumar%20Shukla">Sanjeev Kumar Shukla</a>, <a href="https://publications.waset.org/abstracts/search?q=Govind%20Singh"> Govind Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Prabhat%20Pant%20%20%20%20%20%20Shahzad%20Ahmad"> Prabhat Pant Shahzad Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Graves’ disease is an autoimmune disorder with a genetic predisposition, and CD40 plays a pathogenic role in various autoimmune diseases. A single nucleotide polymorphism at position –1 of the Kozak sequence of the 5 untranslated regions of the CD40 gene of exon 1 has been reported to be associated with the development of Graves’ Disease. Objective: The aim of the present study was to investigate whether CD40 gene polymorphism confers susceptibility to Graves’ disease in the Kumaon region. CD40 gene polymorphisms were studied in Graves’ Disease patients (n=50) and healthy control subjects without anti-thyroid autoantibodies or a family history of autoimmune disorders (n=50). Material and Method: CD40 gene polymorphisms were studied in fifty Graves’ Disease patients and fifty healthy control subjects. All samples were collected from STG Hospital, Haldwani, Nainital. A C/T polymorphism at position –1 of the CD40 gene was measured using the polymerase chain reaction-restriction fragment length polymorphism. Results: There was no significant difference in allele or genotype frequency of the CD40 SNP between Graves’ Disease and control subjects. There was a significant decrease in the TT genotype frequency in the Graves’ Disease patients who developed Graves’ Disease after 40 years old than those under 40 years of age. These data suggest that the SNP of the CD40 gene is associated with susceptibility to the later onset of Graves’ Disease. Conclusion: The CD40 gene was a different susceptibility gene for Graves’ Disease within certain families because it was both linked and associated with Graves’ Disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autoimmune%20%20%20diseases" title="autoimmune diseases">autoimmune diseases</a>, <a href="https://publications.waset.org/abstracts/search?q=pathogenesis" title=" pathogenesis"> pathogenesis</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=therapy" title=" therapy"> therapy</a> </p> <a href="https://publications.waset.org/abstracts/185356/a-ct-polymorphism-at-the-5-untranslated-region-of-cd40-gene-in-patients-associated-with-graves-disease-in-kumaon-region" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185356.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">51</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1485</span> The Identification of Combined Genomic Expressions as a Diagnostic Factor for Oral Squamous Cell Carcinoma</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ki-Yeo%20Kim">Ki-Yeo Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oral%20squamous%20cell%20carcinoma" title="oral squamous cell carcinoma">oral squamous cell carcinoma</a>, <a href="https://publications.waset.org/abstracts/search?q=combined%20biomarker" title=" combined biomarker"> combined biomarker</a>, <a href="https://publications.waset.org/abstracts/search?q=microarray%20dataset" title=" microarray dataset"> microarray dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=correlated%20genes" title=" correlated genes"> correlated genes</a> </p> <a href="https://publications.waset.org/abstracts/35990/the-identification-of-combined-genomic-expressions-as-a-diagnostic-factor-for-oral-squamous-cell-carcinoma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35990.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">423</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1484</span> Correlation of P53 Gene Expression With Serum Alanine Transaminase Levels and Hepatitis B Viral Load in Cirrhosis and Hepatocellular Carcinoma Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Umme%20Shahera">Umme Shahera</a>, <a href="https://publications.waset.org/abstracts/search?q=Saifullah%20Munshi"> Saifullah Munshi</a>, <a href="https://publications.waset.org/abstracts/search?q=Munira%20Jahan"> Munira Jahan</a>, <a href="https://publications.waset.org/abstracts/search?q=Afzalun%20Nessa"> Afzalun Nessa</a>, <a href="https://publications.waset.org/abstracts/search?q=Shahinul%20Alam"> Shahinul Alam</a>, <a href="https://publications.waset.org/abstracts/search?q=Shahina%20Tabassum"> Shahina Tabassum</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of HCC is a multi-stage process. Several extrinsic factors, such as aflatoxin, HBV, nutrition, alcohol, and trace elements are thought to initiate or/and promote the hepatocarcinogenesis. Alteration of p53 status is an important intrinsic factor in this process as p53 is essential for preventing inappropriate cell proliferation and maintaining genome integrity following genotoxic stress. This study was designed to assess the correlation of p53 gene expression with HBV-DNA and serum Alanine transaminase (ALT) in patients with cirrhosis and HCC. The study was conducted among 60 patients. The study population were divided into four groups (15 in each groups)-HBV positive cirrhosis, HBV negative cirrhosis, HBV positive HCC and HBV negative HCC. Expression of p53 gene was observed using real time PCR. P53 gene expressions in the above mentioned groups were correlated with serum ALT level and HBV viral load. p53 gene was significantly higher in HBV-positive patients with HCC than HBV-positive cirrhosis. Similarly, the expression of p53 was significantly higher in HBV-positive HCC than HBV-negative HCC patients. However, the expression of p53 was reduced in HBV-positive cirrhosis in comparison with HBV-negative cirrhosis. P53 gene expression in liver was not correlated with the serum levels of ALT in any of the study groups. HBV- DNA load also did not correlated with p53 gene expression in HBV positive HCC and HBV positive cirrhosis patients. This study shows that there was no significant change with the expression of p53 gene in any of the study groups with ALT level or viral load, though differential expression of p53 gene were observed in cirrhosis and HCC patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=P53" title="P53">P53</a>, <a href="https://publications.waset.org/abstracts/search?q=ALT" title=" ALT"> ALT</a>, <a href="https://publications.waset.org/abstracts/search?q=HBV-DNA" title=" HBV-DNA"> HBV-DNA</a>, <a href="https://publications.waset.org/abstracts/search?q=liver%20cirrhosis" title=" liver cirrhosis"> liver cirrhosis</a>, <a href="https://publications.waset.org/abstracts/search?q=hepatocellular%20carcinoma" title=" hepatocellular carcinoma"> hepatocellular carcinoma</a> </p> <a href="https://publications.waset.org/abstracts/157457/correlation-of-p53-gene-expression-with-serum-alanine-transaminase-levels-and-hepatitis-b-viral-load-in-cirrhosis-and-hepatocellular-carcinoma-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">95</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1483</span> CCR5 as an Ideal Candidate for Immune Gene Therapy and Modification for the Induced Resistance to HIV-1 Infection </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alieh%20Farshbaf">Alieh Farshbaf</a>, <a href="https://publications.waset.org/abstracts/search?q=Tayyeb%20Bahrami"> Tayyeb Bahrami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Cc-chemokine receptor-5 (CCR5) is known as a main co-receptor in human immunodeficiency virus type-1 (HIV-1) infection. Many studies showed 32bp deletion (Δ32) in CCR5 gene, provide natural resistance to HIV-1 infection in homozygous individuals. Inducing the resistance mechanism by CCR5 in HIV-1 infected patients eliminated many problems of highly-active-anti retroviral therapy (HAART) drugs like as low safety, side-effects and virus rebounding from latent reservoirs. New treatments solved some restrictions that are based on gene modification and cell therapy. Literature review: The stories of the “Berlin and Boston patients” showed autologous hematopoietic stem cells transplantation (HSCT) could provide effective cure of HIV-1 infected patients. Furthermore, gene modification by zinc finger nuclease (ZFN) demonstrated another successful result again. Despite the other studies for gene therapy by ∆32 genotype, there is another mutation -CCR5 ∆32/m303- that provides HIV-1 resistant. It is a heterozygote genotype for ∆32 and T→A point mutation at nucleotide 303. These results approved the key role of CCR5 gene. Conclusion: Recent studies showed immune gene therapy and cell therapy could provide effective cure for refractory disease like as HIV. Eradication of HIV-1 from immune system was not observed by HAART, because of reloading virus genome from latent reservoirs after stopping them. It is showed that CCR5 could induce natural resistant to HIV-1 infection by the new approaches based on stem cell transplantation and gene modifying. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CCR5" title="CCR5">CCR5</a>, <a href="https://publications.waset.org/abstracts/search?q=HIV-1" title=" HIV-1"> HIV-1</a>, <a href="https://publications.waset.org/abstracts/search?q=stem%20cell" title=" stem cell"> stem cell</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20gene%20therapy" title=" immune gene therapy"> immune gene therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20modification" title=" gene modification"> gene modification</a> </p> <a href="https://publications.waset.org/abstracts/37333/ccr5-as-an-ideal-candidate-for-immune-gene-therapy-and-modification-for-the-induced-resistance-to-hiv-1-infection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37333.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">290</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1482</span> Pattern Of Polymorphism SLC22A1 Gene In Children With Diabetes Mellitus Type 2</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elly%20Usman">Elly Usman</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Dante"> S. Dante</a>, <a href="https://publications.waset.org/abstracts/search?q=Diah%20Purnamasari"> Diah Purnamasari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Type 2 diabetes mellitus ( T2DM ) is a syndrome characterized by a state of increased blood sugar levels due to chronic disorders of insulin secretion by pancreatic beta cells and insulin action or a combination of both. The organic cation transporter 1, encoded by the SLC22A1 gene, responsible for the uptake of the antihyperglycemic drug, metformin, in the hepatocyte. We assessed whether a genetic variation in the SLC22A1 gene was associated with the glucose - lowering effect of metformin. Method case study research design. Samples are children with type 2 diabetes mellitus who meet the inclusion criteria. The results proportions SLC22A1 gene polymorphisms in children with diabetes mellitus type 2 amounted to 52.04 % at position 400T/C, there is one heterozygous and one at position 595T/C Conclusion The presence of SLC22A1 gene polymorphisms in children with diabetes mellitus type 2. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diabetes%20Mellitus%20type%202" title="diabetes Mellitus type 2">diabetes Mellitus type 2</a>, <a href="https://publications.waset.org/abstracts/search?q=metformin" title=" metformin"> metformin</a>, <a href="https://publications.waset.org/abstracts/search?q=organic%20cation%20transporter%201" title=" organic cation transporter 1"> organic cation transporter 1</a>, <a href="https://publications.waset.org/abstracts/search?q=pharmacogenomics" title=" pharmacogenomics"> pharmacogenomics</a> </p> <a href="https://publications.waset.org/abstracts/3159/pattern-of-polymorphism-slc22a1-gene-in-children-with-diabetes-mellitus-type-2" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3159.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">429</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1481</span> Carriage of 675 4G/5G Polymorphism in PAI-1 Gene and Its Association with Early Pregnancy Losses in Patients with Polycystic Ovary Syndrome</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Komsa-Penkova">R. Komsa-Penkova</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Golemanov"> G. Golemanov</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20Georgieva"> G. Georgieva</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Popovski"> K. Popovski</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Slavov"> N. Slavov</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Ivanov"> P. Ivanov</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Kovacheva"> K. Kovacheva</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Rathee"> S. Rathee</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Konova"> E. Konova</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Blajev"> A. Blajev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Leptin and PAI-1 are important cytokines and may play a role in the regulation of PCOS development. PCOS is frequently associated with obesity, high BMI index and consequently with increased risk of metabolic disorders. The aim of the present study was to evaluate PAI-1 levels, genetic influence of the carriage of 675 4G/5G polymorphism in PAI-1 gene and leptin as a marker of obesity in the development of PCOS. Methods: Genotyping in 84 patients with PCOS and PCO and 100 healthy control subjects to detect single nucleotide deletion 675 G in the promoter of PAI-1 gene. The present study provides evidence that SNP 4G in the PAI-1 gene is associated with early pregnancy losses in patients with polycystosis. Further to this, there is a correlation between leptin levels, PAI-1 levels and BMI in the patients with PCOS, which confirms the role of obesity as a risk factor for PCOS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=carriage%20of%20675%204G%2F5G%20polymorphism" title="carriage of 675 4G/5G polymorphism">carriage of 675 4G/5G polymorphism</a>, <a href="https://publications.waset.org/abstracts/search?q=PCOS" title=" PCOS"> PCOS</a>, <a href="https://publications.waset.org/abstracts/search?q=early%20pregnancy%20losses" title=" early pregnancy losses"> early pregnancy losses</a>, <a href="https://publications.waset.org/abstracts/search?q=PAI-1%20gene" title=" PAI-1 gene"> PAI-1 gene</a> </p> <a href="https://publications.waset.org/abstracts/13903/carriage-of-675-4g5g-polymorphism-in-pai-1-gene-and-its-association-with-early-pregnancy-losses-in-patients-with-polycystic-ovary-syndrome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13903.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">331</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1480</span> Comparison between Effects of Free Curcumin and Curcumin Loaded NIPAAm-MAA Nanoparticles on Telomerase and Pinx1 Gene Expression in Lung Cancer Cells</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Y.%20Pilehvar-Soltanahmadi">Y. Pilehvar-Soltanahmadi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Badrzadeh"> F. Badrzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Zarghami"> N. Zarghami</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Jalilzadeh-Tabrizi"> S. Jalilzadeh-Tabrizi</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Zamani"> R. Zamani </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Herbal compounds such as curcumin which decrease telomerase and gene expression have been considered as beneficial tools for lung cancer treatment. In this article, we compared the effects of pure curcumin and curcumin-loaded NIPAAm-MAA nanoparticles on telomerase and PinX1 gene expression in a lung cancer cell line. A tetrazolium-based assay was used for determination of cytotoxic effects of curcumin on the Calu-6 lung cancer cell line and telomerase and pinX1 gene expression was measured with real-time PCR. MTT assay showed that Curcumin-loaded NIPAAm-MAA inhibited the growth of the Calu-6 lung cancer cell line in a time and dose-dependent manner. Our q-PCR results showed that the expression of telomerase gene was effectively reduced as the concentration of curcumin-loaded NIPAAm-MAA increased while expression of the PinX1 gene became elevated. The results showed that curcumin loaded NIPAAm-MAA exerted cytotoxic effects on the Calu-6 cell line through down-regulation of telomerase and stimulation of pinX1 gene expression. NIPPAm-MAA could be the good carrier for such kinds of hydrophobic agent. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=curcumin" title="curcumin">curcumin</a>, <a href="https://publications.waset.org/abstracts/search?q=NIPAAm-MAA" title=" NIPAAm-MAA"> NIPAAm-MAA</a>, <a href="https://publications.waset.org/abstracts/search?q=PinX1" title=" PinX1"> PinX1</a>, <a href="https://publications.waset.org/abstracts/search?q=telomerase" title=" telomerase"> telomerase</a>, <a href="https://publications.waset.org/abstracts/search?q=lung%20cancer%20cells" title=" lung cancer cells"> lung cancer cells</a> </p> <a href="https://publications.waset.org/abstracts/37740/comparison-between-effects-of-free-curcumin-and-curcumin-loaded-nipaam-maa-nanoparticles-on-telomerase-and-pinx1-gene-expression-in-lung-cancer-cells" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37740.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">301</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1479</span> Wt1 and FoxL2 Genes Expression Pattern in Mesonephros-Gonad Complexes of Green Sea Turtle (Chelonia mydas) Embryos Incubated in Feminization and Masculinization Temperature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fitria%20D.%20Ayuningtyas">Fitria D. Ayuningtyas</a>, <a href="https://publications.waset.org/abstracts/search?q=Anggraini%20Barlian"> Anggraini Barlian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Green turtle (Chelonia mydas) is one of TSD (Temperature-dependent Sex Determination, TSD) animals which sex is determined by the egg’s incubation temperature. GSD (Genotypic Sex Determination) homologous genes such as Wilms’ Tumor (Wt1) and Forkhead Box L2 (FoxL2) play a role in TSD animal sex determination process. Wt1 plays a role in both male pathway, as a transcription factor for Sf1 gene and in female pathway, as a transcription factor for Dax1. FoxL2 plays a role specifically in female sex determination, and known as transcriptional factor for Aromatase gene. Until now, research on the pattern of Wt1 and FoxL2 genes expression in C.mydas has not been conducted yet. The aim of this research is to know the pattern of Wt1 and FoxL2 genes expression in Mesonephros-Gonad (MG) complexes of Chelonia mydas embryos incubated in masculinizing temperature (MT) and feminizing temperature (FT). Eggs of C.mydas incubated in 3 different stage of TSP (Thermosensitive Period) at masculinizing temperature (26±10C, MT) and feminizing temperature (31±10C FT). Mesonefros-gonad complexes were isolated at Pre-TSP stage (FT at days 14th, MT at days 24th), TSP stage (FT at days 24th, MT at days 36th) and differentiated stage (FT at days 40th, MT at days 58th). RNA from mesonephros-gonad (MG) complexes were converted into cDNA by RT-PCR process, and the pattern of Wt1 and FoxL2 genes expression is analyzed by quantitative Real Time PCR (qPCR) method, β-actin gene is used as an internal control. The pattern of Wt1 gene expression in Pre-TSP stage was almost the same between MG complexes incubated at MT or FT, while TSP and differentiation stage, the pattern of Wt1 gene expression in MG complexes incubated at MT or FT was increased. Wt1 gene expression of MG complexes that incubated at FT was higher than at MT. There was a difference pattern between Wt1 gene expression in this research compared to the previous research in protein level. It could be assumed that the difference caused by post-transcriptional regulation mechanisms before mRNA of Wt1 gene translated into protein structure. The pattern of FoxL2 gene expression in Pre-TSP stage was almost the same between MG complexes that incubated at MT and FT, and increased in both TSP and differentiated stage. The FoxL2 gene expression in MG complexes that incubated in FT is higher than MT on TSP and differentiated stage. Based on the results of this research, it can be assumed that Wt1 and FoxL2 gene were expressed in MG complexes that incubated both at MT and FT since Pre-TSP stage. The pattern of Wt1 gene expression was increased in every stage of gonadal development, and so do the pattern of FoxL2 gene expression. Wt1 and FoxL2 gene expressions were higher in MG complexes incubated at FT than MT. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chelonia%20mydas" title="chelonia mydas">chelonia mydas</a>, <a href="https://publications.waset.org/abstracts/search?q=FoxL2" title=" FoxL2"> FoxL2</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression" title=" gene expression"> gene expression</a>, <a href="https://publications.waset.org/abstracts/search?q=TSD" title=" TSD"> TSD</a>, <a href="https://publications.waset.org/abstracts/search?q=Wt1" title=" Wt1"> Wt1</a> </p> <a href="https://publications.waset.org/abstracts/15175/wt1-and-foxl2-genes-expression-pattern-in-mesonephros-gonad-complexes-of-green-sea-turtle-chelonia-mydas-embryos-incubated-in-feminization-and-masculinization-temperature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15175.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=50">50</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=51">51</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=FMR1%20gene&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>