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gene</title> <meta name="description" content="Search results for: Calmodulin gene"> <meta name="keywords" content="Calmodulin 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 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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="Calmodulin 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> 1519</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Calmodulin gene</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1519</span> Transcriptomic Response of Calmodulin Encoding Gene (CaM) in Pesticide Utilizing Talaromyces Fungal Strains </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20D.%20Asemoloye">M. D. Asemoloye</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20G.%20Jonathan"> S. G. Jonathan</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Rafiq"> A. Rafiq</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20J.%20Olawuyi"> O. J. Olawuyi</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20O.%20Adejoye"> D. O. Adejoye</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Calmodulin is one of the intracellular calcium proteins that regulates large spectrum of enzymes and cellular functions including metabolism of cyclic nucleotides and glycogen. The potentials of calmodulin gene in fungi necessitates their genetic response and their strong cassette of enzyme secretions for pesticide degradation. Therefore, this study was carried out to investigate the ‘Transcriptomic’ response of calmodulin encoding genes in Talaromyces fungi in response to 2, 2-dichlorovinyl dimethyl phosphate (DDVP or Dichlorvos) an organophosphate pesticide and γ-Hexachlorocyclohexane (Lindane) an organochlorine pesticide. Fungi strains isolated from rhizosphere from grasses rhizosphere in pesticide polluted sites were subjected to percentage incidence test. Two most frequent fungi were further characterized using ITS gene amplification (ITS1 and ITS4 combinations), they were thereafter subjected to In-vitro DDVP and lindane tolerance tests at different concentrations. They were also screened for presence and expression of calmodulin gene (caM) using RT-PCR technique. The two Talaromyces strains had the highest incidence of 50-72% in pesticide polluted site, they were both identified as Talaromyces astroroseus asemoG and Talaromyces purpurogenum asemoN submitted in NCBI gene-bank with accession numbers KY488464 and KY488468 respectively. T. astroroseus KY488464 tolerated DDVP (1.23±0.023 cm) and lindane (1.11±0.018 cm) at 25 % concentration while T. purpurogenum KY488468 tolerated DDVP (1.33±0.061 cm) and lindane (1.54±0.077 cm) at this concentration. Calmodulin gene was detected in both strains, but RT-PCR expression of caM gene revealed at 900-1000 bp showed an under-expression of caM in T. astrorosues KY488464 but overexpressed in T. purpurogenum KY488464. Thus, the calmodulin gene response of these fungal strains to both pesticides could be considered in monitoring the potentials of fungal strains to pesticide tolerance and bioremediation of pesticide in polluted soil. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Calmodulin%20gene" title="Calmodulin gene">Calmodulin gene</a>, <a href="https://publications.waset.org/abstracts/search?q=pesticide" title=" pesticide"> pesticide</a>, <a href="https://publications.waset.org/abstracts/search?q=RT-PCR" title=" RT-PCR"> RT-PCR</a>, <a href="https://publications.waset.org/abstracts/search?q=talaromyces" title=" talaromyces"> talaromyces</a>, <a href="https://publications.waset.org/abstracts/search?q=tolerance" title=" tolerance"> tolerance</a> </p> <a href="https://publications.waset.org/abstracts/77765/transcriptomic-response-of-calmodulin-encoding-gene-cam-in-pesticide-utilizing-talaromyces-fungal-strains" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77765.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">225</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">1518</span> Effect of Removing Hub Domain on Human CaMKII Isoforms Sensitivity to Calcium/Calmodulin</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ravid%20Inbar">Ravid Inbar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> CaMKII (calcium-calmodulin dependent protein kinase II) makes up 2% of the protein in our brain and has a critical role in memory formation and long-term potentiation of neurons. Despite this, research has yet to uncover the role of one of the domains on the activation of this kinase. The following proposes to express the protein without the hub domain in E. coli, leaving only the kinase and regulatory segment of the protein. Next, a series of kinase assays will be conducted to elucidate the role the hub domain plays on CaMKII sensitivity to calcium/calmodulin activation. The hub domain may be important for activation; however, it may also be a variety of domains working together to influence protein activation and not the hub alone. Characterization of a protein is critical to the future understanding of the protein's function, as well as for producing pharmacological targets in cases of patients with diseases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CaMKII" title="CaMKII">CaMKII</a>, <a href="https://publications.waset.org/abstracts/search?q=hub%20domain" title=" hub domain"> hub domain</a>, <a href="https://publications.waset.org/abstracts/search?q=kinase%20assays" title=" kinase assays"> kinase assays</a>, <a href="https://publications.waset.org/abstracts/search?q=kinase%20%2B%20reg%20seg" title=" kinase + reg seg"> kinase + reg seg</a> </p> <a href="https://publications.waset.org/abstracts/157748/effect-of-removing-hub-domain-on-human-camkii-isoforms-sensitivity-to-calciumcalmodulin" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157748.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">1517</span> Rational Design of Potent Compounds for Inhibiting Ca2+ -Dependent Calmodulin Kinase IIa, a Target of Alzheimer’s Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Son%20Nguyen">Son Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Thanh%20Van"> Thanh Van</a>, <a href="https://publications.waset.org/abstracts/search?q=Ly%20Le"> Ly Le</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ca2+ - dependent calmodulin kinase IIa (CaMKIIa) has recently been found to associate with protein tau missorting and polymerization in Alzheimer’s Disease (AD). However, there has yet inhibitors targeting CaMKIIa to investigate the correlation between CaMKIIa activity and protein tau polymer formation. Combining virtual screening and our statistics in binding contribution scoring function (BCSF), we rationally identified potential compounds that bind to specific CaMKIIa active site and specificity-affinity distribution of the ligand within the active site. Using molecular dynamics simulation, we identified structural stability of CaMKIIa and potent inhibitors, and site-directed bonding, separating non-specific and specific molecular interaction features. Despite of variation in confirmation of simulation time, interactions of the potent inhibitors were found to be strongly associated with the unique chemical features extracted from molecular binding poses. In addition, competitive inhibitors within CaMKIIa showed an important molecular recognition pattern toward specific ligand features. Our approach combining virtual screening with BCSF may provide an universally applicable method for precise identification in the discovery of compounds. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alzheimer%E2%80%99s%20disease" title="Alzheimer’s disease">Alzheimer’s disease</a>, <a href="https://publications.waset.org/abstracts/search?q=Ca%202%2B%20-dependent%20calmodulin%20kinase%20IIa" title=" Ca 2+ -dependent calmodulin kinase IIa"> Ca 2+ -dependent calmodulin kinase IIa</a>, <a href="https://publications.waset.org/abstracts/search?q=protein%20tau" title=" protein tau"> protein tau</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20docking" title=" molecular docking"> molecular docking</a> </p> <a href="https://publications.waset.org/abstracts/84655/rational-design-of-potent-compounds-for-inhibiting-ca2-dependent-calmodulin-kinase-iia-a-target-of-alzheimers-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84655.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">274</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">1516</span> Genome-Wide Identification and Characterization of MLO Family Genes in Pumpkin (Cucurbita maxima Duch.)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khin%20Thanda%20Win">Khin Thanda Win</a>, <a href="https://publications.waset.org/abstracts/search?q=Chunying%20Zhang"> Chunying Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanghyeob%20Lee"> Sanghyeob Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mildew resistance locus o (Mlo), a plant-specific gene family with seven-transmembrane (TM), plays an important role in plant resistance to powdery mildew (PM). PM caused by Podosphaera xanthii is a widespread plant disease and probably represents the major fungal threat for many Cucurbits. The recent Cucurbita maxima genome sequence data provides an opportunity to identify and characterize the MLO gene family in this species. Total twenty genes (designated CmaMLO1 through CmaMLO20) have been identified by using an in silico cloning method with the MLO gene sequences of Cucumis sativus, Cucumis melo, Citrullus lanatus and Cucurbita pepo as probes. These CmaMLOs were evenly distributed on 15 chromosomes of 20 C. maxima chromosomes without any obvious clustering. Multiple sequence alignment showed that the common structural features of MLO gene family, such as TM domains, a calmodulin-binding domain and 30 important amino acid residues for MLO function, were well conserved. Phylogenetic analysis of the CmaMLO genes and other plant species reveals seven different clades (I through VII) and only clade IV is specific to monocots (rice, barley, and wheat). Phylogenetic and structural analyses provided preliminary evidence that five genes belonged to clade V could be the susceptibility genes which may play the importance role in PM resistance. This study is the first comprehensive report on MLO genes in C. maxima to our knowledge. These findings will facilitate the functional analysis of the MLOs related to PM susceptibility and are valuable resources for the development of disease resistance in pumpkin. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mildew%20resistance%20locus%20o%20%28Mlo%29" title="Mildew resistance locus o (Mlo)">Mildew resistance locus o (Mlo)</a>, <a href="https://publications.waset.org/abstracts/search?q=powdery%20mildew" title=" powdery mildew"> powdery mildew</a>, <a href="https://publications.waset.org/abstracts/search?q=phylogenetic%20relationship" title=" phylogenetic relationship"> phylogenetic relationship</a>, <a href="https://publications.waset.org/abstracts/search?q=susceptibility%20genes" title=" susceptibility genes"> susceptibility genes</a> </p> <a href="https://publications.waset.org/abstracts/75919/genome-wide-identification-and-characterization-of-mlo-family-genes-in-pumpkin-cucurbita-maxima-duch" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75919.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">181</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">1515</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">1514</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">1513</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">325</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">1512</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">1511</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">1510</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">279</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">1509</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">309</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">1508</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">1507</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">1506</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">404</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> 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">1504</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">1503</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">1502</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">612</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> 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">293</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> 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">1499</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">1498</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">1497</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">1496</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">1495</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">1494</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">1493</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">1492</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">1491</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">1490</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> <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=Calmodulin%20gene&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Calmodulin%20gene&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Calmodulin%20gene&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=Calmodulin%20gene&page=5">5</a></li> <li class="page-item"><a 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