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expression</title> <meta name="description" content="Search results for: gene expression"> <meta name="keywords" content="gene expression"> <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 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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="gene expression"> <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> 2928</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: gene expression</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2928</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">2927</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">2926</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">2925</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">2924</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">2923</span> A Novel PfkB Gene Cloning and Characterization for Expression in Potato Plants</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arfan%20Ali">Arfan Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Idrees%20Ahmad%20Nasir"> Idrees Ahmad Nasir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Potato (Solanum tuberosum) is an important cash crop and popular vegetable in Pakistan and throughout the world. Cold storage of potatoes accelerates the conversion of starch into reduced sugars (glucose and fructose). This process causes dry mass and bitter taste in the potatoes that are not acceptable to end consumers. In the current study, the phosphofructokinase B gene was cloned into the pET-30 vector for protein expression and the pCambia-1301 vector for plant expression. Amplification of a 930bp product from an E. coli strain determined the successful isolation of the phosphofructokinase B gene. Restriction digestion using NcoI and BglII along with the amplification of the 930bp product using gene specific primers confirmed the successful cloning of the PfkB gene in both vectors. The protein was expressed as a His-PfkB fusion protein. Western blot analysis confirmed the presence of the 35 Kda PfkB protein when hybridized with anti-His antibodies. The construct Fani-01 was evaluated transiently using a histochemical gus assay. The appearance of blue color in the agroinfiltrated area of potato leaves confirmed the successful expression of construct Fani-01. Further, the area displaying gus expression was evaluated for PfkB expression using ELISA. Moreover, PfkB gene expression evaluated through transient expression determined successful gene expression and highlighted its potential utilization for stable expression in potato to reduce sweetening due to long-term storage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=potato" title="potato">potato</a>, <a href="https://publications.waset.org/abstracts/search?q=Solanum%20tuberosum" title=" Solanum tuberosum"> Solanum tuberosum</a>, <a href="https://publications.waset.org/abstracts/search?q=transformation" title=" transformation"> transformation</a>, <a href="https://publications.waset.org/abstracts/search?q=PfkB" title=" PfkB"> PfkB</a>, <a href="https://publications.waset.org/abstracts/search?q=anti-sweetening" title=" anti-sweetening "> anti-sweetening </a> </p> <a href="https://publications.waset.org/abstracts/24921/a-novel-pfkb-gene-cloning-and-characterization-for-expression-in-potato-plants" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24921.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">472</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">2922</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">2921</span> Analysis of Expression Data Using Unsupervised Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20I%20Perera">M. A. I Perera</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20R.%20Wijesinghe"> C. R. Wijesinghe</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20R.%20%20Weerasinghe"> A. R. Weerasinghe</a> </p> <p class="card-text"><strong>Abstract:</strong></p> his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cancer%20subtypes" title="cancer subtypes">cancer subtypes</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression%20data%20analysis" title=" gene expression data analysis"> gene expression data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster%20validation" title=" cluster validation"> cluster validation</a> </p> <a href="https://publications.waset.org/abstracts/129027/analysis-of-expression-data-using-unsupervised-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129027.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">149</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">2920</span> Pathway and Differential Gene Expression Studies for Colorectal Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ankita%20Shukla">Ankita Shukla</a>, <a href="https://publications.waset.org/abstracts/search?q=Tiratha%20Raj%20Singh"> Tiratha Raj Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Colorectal cancer (CRC) imposes serious mortality burden worldwide and it has been increasing for past consecutive years. Continuous efforts have been made so far to diagnose the disease condition and to identify the root cause for it. In this study, we performed the pathway level as well as the differential gene expression studies for CRC. We analyzed the gene expression profile GSE24514 from Gene Expression Omnibus (GEO) along with the gene pathways involved in the CRC. This analysis helps us to understand the behavior of the genes that have shown differential expression through their targeted pathways. Pathway analysis for the targeted genes covers the wider area which therefore decreases the possibility to miss the significant ones. This will prove to be beneficial to expose the ones that have not been given attention so far. Through this analysis, we attempt to understand the various neighboring genes that have close relationship to the targeted one and thus proved to be significantly controlling the CRC. It is anticipated that the identified hub and neighboring genes will provide new directions to look at the pathway level differently and will be crucial for the regulatory processes of the disease. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mismatch%20repair" title="mismatch repair">mismatch repair</a>, <a href="https://publications.waset.org/abstracts/search?q=microsatellite%20instability" title=" microsatellite instability"> microsatellite instability</a>, <a href="https://publications.waset.org/abstracts/search?q=carcinogenesis" title=" carcinogenesis"> carcinogenesis</a>, <a href="https://publications.waset.org/abstracts/search?q=morbidity" title=" morbidity"> morbidity</a> </p> <a href="https://publications.waset.org/abstracts/63300/pathway-and-differential-gene-expression-studies-for-colorectal-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63300.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">320</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">2919</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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2918</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">2917</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">2916</span> Assessing the Correlation between miR-141 Expression, Common K-Ras Gene Mutations, and Their Impact on Prognosis in Colorectal Cancer Tissue of Iranian Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shima%20Behzadi">Shima Behzadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: In many human malignant tumors, microRNA expression is aberrant. This study investigates miR-141 as a prognostic marker in colorectal cancer with K-Ras mutation. Materials and methods: In this case-control study, 100 patients, mostly over the age of 50, who were diagnosed with colorectal cancer were selected. The pathology department of the Mostoufi Pathobiology and Genetics Laboratory in Tehran confirmed the presence of colorectal cancer in samples of paraffin-embedded colon tissue. The case group was composed of patients with codon 12 and 13 mutations in exon 2 of the K-Ras gene, while tumor samples of individuals without these mutations in exon 2 of the K-Ras gene were selected as the control group, with patient consent. The changes in the expression of miR-141 were examined in both groups. Results: The study found that 20% of the patients tested positive for codon 12 mutation, and 10% of patients had codon 13 mutation. As a result, in 30 cases, there was a higher level of miR-141 expression. The miR-141 gene expression level in K-Ras positive tumor samples was 1.5 times higher than its expression level in K-Ras negative samples. This increase in expression was statistically significant, with a p-value of less than 0.001, indicating that the observed results are highly statistically significant. Conclusion: The study revealed that the incidence of typical K-Ras gene mutations among the colorectal cancer patients in the sample matches the national average in Iran. Additionally, the expression of miR-141 can serve as a useful biomarker to aid in the prognosis of colorectal cancer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=colorectal%20cancer" title="colorectal cancer">colorectal cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=K-Ras%20gene" title=" K-Ras gene"> K-Ras gene</a>, <a href="https://publications.waset.org/abstracts/search?q=miR-141%20marker" title=" miR-141 marker"> miR-141 marker</a>, <a href="https://publications.waset.org/abstracts/search?q=real%20time%20PCR" title=" real time PCR"> real time PCR</a>, <a href="https://publications.waset.org/abstracts/search?q=electrophoresis" title=" electrophoresis"> electrophoresis</a> </p> <a href="https://publications.waset.org/abstracts/188255/assessing-the-correlation-between-mir-141-expression-common-k-ras-gene-mutations-and-their-impact-on-prognosis-in-colorectal-cancer-tissue-of-iranian-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188255.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">43</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">2915</span> Robustness Conditions for the Establishment of Stationary Patterns of Drosophila Segmentation Gene Expression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ekaterina%20M.%20Myasnikova">Ekaterina M. Myasnikova</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrey%20A.%20Makashov"> Andrey A. Makashov</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20V.%20Spirov"> Alexander V. Spirov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> First manifestation of a segmentation pattern in the early Drosophila development is the formation of expression domains (along with the main embryo axis) of genes belonging to the trunk gene class. Highly variable expression of genes from gap family in early Drosophila embryo is strongly reduced by the start of gastrulation due to the gene cross-regulation. The dynamics of gene expression is described by a gene circuit model for a system of four gap genes. It is shown that for the formation of a steep and stationary border by the model it is necessary that there existed a nucleus (modeling point) in which the gene expression level is constant in time and hence is described by a stationary equation. All the rest genes expressed in this nucleus are in a dynamic equilibrium. The mechanism of border formation associated with the existence of a stationary nucleus is also confirmed by the experiment. An important advantage of this approach is that properties of the system in a stationary nucleus are described by algebraic equations and can be easily handled analytically. Thus we explicitly characterize the cross-regulation properties necessary for the robustness and formulate the conditions providing this effect through the properties of the initial input data. It is shown that our formally derived conditions are satisfied for the previously published model solutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drosophila" title="drosophila">drosophila</a>, <a href="https://publications.waset.org/abstracts/search?q=gap%20genes" title=" gap genes"> gap genes</a>, <a href="https://publications.waset.org/abstracts/search?q=reaction-diffusion%20model" title=" reaction-diffusion model"> reaction-diffusion model</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness" title=" robustness"> robustness</a> </p> <a href="https://publications.waset.org/abstracts/73794/robustness-conditions-for-the-establishment-of-stationary-patterns-of-drosophila-segmentation-gene-expression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73794.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">366</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">2914</span> Biophysically Motivated Phylogenies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Catherine%20Felce">Catherine Felce</a>, <a href="https://publications.waset.org/abstracts/search?q=Lior%20Pachter"> Lior Pachter</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Current methods for building phylogenetic trees from gene expression data consider mean expression levels. With single-cell technologies, we can leverage more information about cell dynamics by considering the entire distribution of gene expression across cells. Using biophysical modeling, we propose a method for constructing phylogenetic trees from scRNA-seq data, building on Felsenstein's method of continuous characters. This method can highlight genes whose level of expression may be unchanged between species, but whose rates of transcription/decay may have evolved over time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=phylogenetics" title="phylogenetics">phylogenetics</a>, <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=biophysical%20modeling" title=" biophysical modeling"> biophysical modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=transcription" title=" transcription"> transcription</a> </p> <a href="https://publications.waset.org/abstracts/186016/biophysically-motivated-phylogenies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186016.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">49</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">2913</span> An Analysis on Clustering Based Gene Selection and Classification for Gene Expression Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Sathishkumar">K. Sathishkumar</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Thiagarasu">V. Thiagarasu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microarray%20technology" title="microarray technology">microarray technology</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=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20Selection" title=" gene Selection"> gene Selection</a> </p> <a href="https://publications.waset.org/abstracts/27523/an-analysis-on-clustering-based-gene-selection-and-classification-for-gene-expression-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27523.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">323</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">2912</span> Cloning and Expression of the ansZ Gene from Bacillus sp. CH11 Isolated from Chilca salterns in Peru</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Stephy%20Saavedra">Stephy Saavedra</a>, <a href="https://publications.waset.org/abstracts/search?q=Annsy%20C.%20Arredondo"> Annsy C. Arredondo</a>, <a href="https://publications.waset.org/abstracts/search?q=Gisele%20Monteiro"> Gisele Monteiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Adalberto%20Pessoa%20Jr"> Adalberto Pessoa Jr</a>, <a href="https://publications.waset.org/abstracts/search?q=Carol%20N.%20Flores-Fernandez"> Carol N. Flores-Fernandez</a>, <a href="https://publications.waset.org/abstracts/search?q=Amparo%20I.%20Zavaleta"> Amparo I. Zavaleta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> L-asparaginase from bacterial sources is used in leukemic treatment and food industry. This enzyme is classified based on its affinity towards L-asparagine and L-glutamine. Likewise, ansZ genes express L-asparaginase with higher affinity to L-asparagine. The aim of this work was to clone and express of ansZ gene from Bacillus sp. CH11 isolated from Chilca salterns in Peru. The gene encoding L-asparaginase was cloned into pET15b vector and transformed in Escherichia coli BL21 (DE3) pLysS. The expression was carried out in a batch culture using LB broth and 0.5 mM IPTG. The recombinant L-asparaginase showed a molecular weight of ~ 39 kDa by SDS PAGE and a specific activity of 3.19 IU/mg of protein. The cloning and expression of ansZ gene from this halotolerant Bacillus sp. CH11 allowed having a biological input to improve a future scaling-up. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ansZ%20gene" title="ansZ gene">ansZ gene</a>, <a href="https://publications.waset.org/abstracts/search?q=Bacillus%20sp" title=" Bacillus sp"> Bacillus sp</a>, <a href="https://publications.waset.org/abstracts/search?q=Chilca%20salterns" title=" Chilca salterns"> Chilca salterns</a>, <a href="https://publications.waset.org/abstracts/search?q=recombinant%20L-asparaginase" title=" recombinant L-asparaginase"> recombinant L-asparaginase</a> </p> <a href="https://publications.waset.org/abstracts/141113/cloning-and-expression-of-the-ansz-gene-from-bacillus-sp-ch11-isolated-from-chilca-salterns-in-peru" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141113.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">179</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">2911</span> The Expression of Lipoprotein Lipase Gene with Fat Accumulations and Serum Biochemical Levels in Betong (KU Line) and Broiler Chickens</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=W.%20Loongyai">W. Loongyai</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Saengsawang"> N. Saengsawang</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20Danvilai"> W. Danvilai</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Kridtayopas"> C. Kridtayopas</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Sopannarath"> P. Sopannarath</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Bunchasak"> C. Bunchasak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Betong chicken is a slow growing and a lean strain of chicken, while the rapid growth of broiler is accompanied by increased fat. We investigated the growth performance, fat accumulations, lipid serum biochemical levels and lipoprotein lipase (LPL) gene expression of female Betong (KU line) at the age of 4 and 6 weeks. A total of 80 female Betong chickens (KU line) and 80 female broiler chickens were reared under open system (each group had 4 replicates of 20 chicks per pen). The results showed that feed intake and average daily gain (ADG) of broiler chicken were significantly higher than Betong (KU line) (P < 0.01), while feed conversion ratio (FCR) of Betong (KU line) at week 6 were significantly lower than broiler chicken (P < 0.01) at 6 weeks. At 4 and 6 weeks, two birds per replicate were randomly selected and slaughtered. Carcass weight did not significantly differ between treatments; the percentage of abdominal fat and subcutaneous fat yield was higher in the broiler (P < 0.01) at 4 and 6 week. Total cholesterol and LDL level of broiler were higher than Betong (KU line) at 4 and 6 weeks (P < 0.05). Abdominal fat samples were collected for total RNA extraction. The cDNA was amplified using primers specific for LPL gene expression and analysed using real-time PCR. The results showed that the expression of LPL gene was not different when compared between Betong (KU line) and broiler chickens at the age of 4 and 6 weeks (P > 0.05). Our results indicated that broiler chickens had high growth rate and fat accumulation when compared with Betong (KU line) chickens, whereas LPL gene expression did not differ between breeds. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lipoprotein%20lipase%20gene" title="lipoprotein lipase gene">lipoprotein lipase gene</a>, <a href="https://publications.waset.org/abstracts/search?q=Betong%20%28KU%20line%29" title=" Betong (KU line)"> Betong (KU line)</a>, <a href="https://publications.waset.org/abstracts/search?q=broiler" title=" broiler"> broiler</a>, <a href="https://publications.waset.org/abstracts/search?q=abdominal%20fat" title=" abdominal fat"> abdominal fat</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression" title=" gene expression"> gene expression</a> </p> <a href="https://publications.waset.org/abstracts/96914/the-expression-of-lipoprotein-lipase-gene-with-fat-accumulations-and-serum-biochemical-levels-in-betong-ku-line-and-broiler-chickens" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96914.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">2910</span> Quantitative Evaluation of Endogenous Reference Genes for ddPCR under Salt Stress Using a Moderate Halophile</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qinghua%20Xing">Qinghua Xing</a>, <a href="https://publications.waset.org/abstracts/search?q=Noha%20M.%20Mesbah"> Noha M. Mesbah</a>, <a href="https://publications.waset.org/abstracts/search?q=Haisheng%20Wang"> Haisheng Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jun%20Li"> Jun Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Baisuo%20Zhao"> Baisuo Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Droplet digital PCR (ddPCR) is being increasingly adopted for gene detection and quantification because of its higher sensitivity and specificity. According to previous observations and our lab data, it is essential to use endogenous reference genes (RGs) when investigating gene expression at the mRNA level under salt stress. This study aimed to select and validate suitable RGs for gene expression under salt stress using ddPCR. Six candidate RGs were selected based on the tandem mass tag (TMT)-labeled quantitative proteomics of Alkalicoccus halolimnae at four salinities. The expression stability of these candidate genes was evaluated using statistical algorithms (geNorm, NormFinder, BestKeeper and RefFinder). There was a small fluctuation in cycle threshold (Ct) value and copy number of the pdp gene. Its expression stability was ranked in the vanguard of all algorithms, and was the most suitable RG for quantification of expression by both qPCR and ddPCR of A. halolimnae under salt stress. Single RG pdp and RG combinations were used to normalize the expression of ectA, ectB, ectC, and ectD under four salinities. The present study constitutes the first systematic analysis of endogenous RG selection for halophiles responding to salt stress. This work provides a valuable theory and an approach reference of internal control identification for ddPCR-based stress response models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=endogenous%20reference%20gene" title="endogenous reference gene">endogenous reference gene</a>, <a href="https://publications.waset.org/abstracts/search?q=salt%20stress" title=" salt stress"> salt stress</a>, <a href="https://publications.waset.org/abstracts/search?q=ddPCR" title=" ddPCR"> ddPCR</a>, <a href="https://publications.waset.org/abstracts/search?q=RT-qPCR" title=" RT-qPCR"> RT-qPCR</a>, <a href="https://publications.waset.org/abstracts/search?q=Alkalicoccus%20halolimnae" title=" Alkalicoccus halolimnae"> Alkalicoccus halolimnae</a> </p> <a href="https://publications.waset.org/abstracts/165112/quantitative-evaluation-of-endogenous-reference-genes-for-ddpcr-under-salt-stress-using-a-moderate-halophile" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165112.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">104</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">2909</span> Investigation of FoxM1 Gene Expression in Breast Cancer and Its Relationship with miR-216b-5p Expression Level</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Neda%20Menbari">Neda Menbari</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramin%20Mehdiabadi"> Ramin Mehdiabadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: breast cancer remains a critical global health issue, constituting a leading cause of cancer-related mortality in women. MicroRNAs (miRs) are natural RNA molecules that play an important role in cellular processes and regulate post-transcriptional gene expression. MiR-216b-5p is a miR that acts as a tumor suppressor. The expression levels of FoxM1 and miR-216b-5p in malignant and control cells have been evaluated by quantitative polymerase chain reaction (qPCR) technique and flow cytometry. Results: the results of this study revealed a significant downregulation of miR-216b-5p in cancerous cells compared to the control MCF-10A cells (P=0.0004). Interestingly, the expression of miR-216b-5p exhibited an inverse relationship with key clinical indicators such as tumor size, grade, and lymph node invasion. Conclusion: The study's findings showed the prognostic value of miR-216b-5p levels in breast cancer, and its reduced expression correlates with unfavorable tumor characteristics. This research recommends performing more studies on the role of FoxM1 and miR-216b-5p in breast cancer pathology which potentially paving the way for targeted therapeutic interventions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</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=FOXM1" title=" FOXM1"> FOXM1</a>, <a href="https://publications.waset.org/abstracts/search?q=microRNA" title=" microRNA"> microRNA</a> </p> <a href="https://publications.waset.org/abstracts/185448/investigation-of-foxm1-gene-expression-in-breast-cancer-and-its-relationship-with-mir-216b-5p-expression-level" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185448.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">52</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">2908</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">2907</span> An Analysis System for Integrating High-Throughput Transcript Abundance Data with Metabolic Pathways in Green Algae</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Han-Qin%20Zheng">Han-Qin Zheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Yi-Fan%20Chiang-Hsieh"> Yi-Fan Chiang-Hsieh</a>, <a href="https://publications.waset.org/abstracts/search?q=Chia-Hung%20Chien"> Chia-Hung Chien</a>, <a href="https://publications.waset.org/abstracts/search?q=Wen-Chi%20Chang"> Wen-Chi Chang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the most important non-vascular plants, algae have many research applications, including high species diversity, biofuel sources, adsorption of heavy metals and, following processing, health supplements. With the increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes, an integrated resource for retrieving gene expression data and metabolic pathway is essential for functional analysis and systems biology in algae. However, gene expression profiles and biological pathways are displayed separately in current resources, and making it impossible to search current databases directly to identify the cellular response mechanisms. Therefore, this work develops a novel AlgaePath database to retrieve gene expression profiles efficiently under various conditions in numerous metabolic pathways. AlgaePath, a web-based database, integrates gene information, biological pathways, and next-generation sequencing (NGS) datasets in Chlamydomonasreinhardtii and Neodesmus sp. UTEX 2219-4. Users can identify gene expression profiles and pathway information by using five query pages (i.e. Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-Expression Analysis). The gene expression data of 45 and 4 samples can be obtained directly on pathway maps in C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively. Genes that are differentially expressed between two conditions can be identified in Folds Search. Furthermore, the Gene Group Analysis of AlgaePath includes pathway enrichment analysis, and can easily compare the gene expression profiles of functionally related genes in a map. Finally, Co-Expression Analysis provides co-expressed transcripts of a target gene. The analysis results provide a valuable reference for designing further experiments and elucidating critical mechanisms from high-throughput data. More than an effective interface to clarify the transcript response mechanisms in different metabolic pathways under various conditions, AlgaePath is also a data mining system to identify critical mechanisms based on high-throughput sequencing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=next-generation%20sequencing%20%28NGS%29" title="next-generation sequencing (NGS)">next-generation sequencing (NGS)</a>, <a href="https://publications.waset.org/abstracts/search?q=algae" title=" algae"> algae</a>, <a href="https://publications.waset.org/abstracts/search?q=transcriptome" title=" transcriptome"> transcriptome</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20pathway" title=" metabolic pathway"> metabolic pathway</a>, <a href="https://publications.waset.org/abstracts/search?q=co-expression" title=" co-expression"> co-expression</a> </p> <a href="https://publications.waset.org/abstracts/9022/an-analysis-system-for-integrating-high-throughput-transcript-abundance-data-with-metabolic-pathways-in-green-algae" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9022.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> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2906</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">2905</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">2904</span> Study on Developmental and Pathogenesis Related Genes Expression Deregulation in Brassica compestris Infected with 16Sr-IX Associated Phytoplasma </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samina%20Jam%20Nazeer%20Ahmad">Samina Jam Nazeer Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Samia%20%20Yasin"> Samia Yasin</a>, <a href="https://publications.waset.org/abstracts/search?q=Ijaz%20Ahmad"> Ijaz Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Tahir"> Muhammad Tahir</a>, <a href="https://publications.waset.org/abstracts/search?q=Jam%20Nazeer%20Ahmad"> Jam Nazeer Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Phytoplasmas are phloem-inhibited plant pathogenic bacteria that are transferred by insect vectors. Among biotic factors, Phytoplasma infection induces abnormality influencing the physiology as well as morphology of plants. In 16Sr-IX group phytoplasma-infected brassica compestris, flower abnormalities have been associated with changes in the expression of floral development genes. To determine whether methylation was involved in down-regulation of flower development, the process of DNA methylation and Demethylation was investigated as a possible mechanism for regulation of floral gene expression in phytoplasma infected Brassica transmitted by Orosious orientalis vector by using RT-PCR, MSRE-PCR, Southern blotting, Bisulfite Sequencing, etc. Transcriptional expression of methylated genes was found to be globally down-regulated in plants infected with phytoplasma, but not severely in those infested by insect vectors and variation in expression was found in genes involved in methylation. These results also showed that genes particularly orthologous to Arabidopsis APETALA3 involved in petal formation and flower development was down-regulated severely in phytoplasma-infected brassica and with the fact that phytoplasma and insect induce variation in developmental gene expression. The DNA methylation status of flower developmental gene in phytoplasma infected plants with 5-azacytidine restored gene expression strongly suggesting that DNA methylation was involved in down-regulation of floral development genes in phytoplasma infected brassica. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=genes%20expression" title="genes expression">genes expression</a>, <a href="https://publications.waset.org/abstracts/search?q=phytoplasma" title=" phytoplasma"> phytoplasma</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20methylation" title=" DNA methylation"> DNA methylation</a>, <a href="https://publications.waset.org/abstracts/search?q=flower%20development" title=" flower development"> flower development</a> </p> <a href="https://publications.waset.org/abstracts/87401/study-on-developmental-and-pathogenesis-related-genes-expression-deregulation-in-brassica-compestris-infected-with-16sr-ix-associated-phytoplasma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87401.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">374</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">2903</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">2902</span> Cloning and Expression of Human Interleukin 15: A Promising Candidate for Cytokine Immunotherapy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sadaf%20Ilyas">Sadaf Ilyas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recombinant cytokines have been employed successfully as potential therapeutic agent. Some cytokine therapies are already used as a part of clinical practice, ranging from early exploratory trials to well established therapies that have already received approval. Interleukin 15 is a pleiotropic cytokine having multiple roles in peripheral innate and adaptive immune cell function. It regulates the activation, proliferation and maturation of NK cells, T-cells, monocytes/macrophages and granulocytes, and the interactions between them thus acting as a bridge between innate and adaptive immune responses. Unraveling the biology of IL-15 has revealed some interesting surprises that may point toward some of the first therapeutic applications for this cytokine. In this study, the human interleukin 15 gene was isolated, amplified and ligated to a TA vector which was then transfected to a bacterial host, E. coli Top10F’. The sequence of cloned gene was confirmed and it showed 100% homology with the reported sequence. The confirmed gene was then subcloned in pET Expression system to study the IPTG induced expression of IL-15 gene. Positive expression was obtained for number of clones that showed 15 kd band of IL-15 in SDS-PAGE analysis, indicating the successful strain development that can be studied further to assess the potential therapeutic intervention of this cytokine in relevance to human diseases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Interleukin%2015" title="Interleukin 15">Interleukin 15</a>, <a href="https://publications.waset.org/abstracts/search?q=pET%20expression%20system" title=" pET expression system"> pET expression system</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20therapy" title=" immune therapy"> immune therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=protein%20purification" title=" protein purification"> protein purification</a> </p> <a href="https://publications.waset.org/abstracts/43003/cloning-and-expression-of-human-interleukin-15-a-promising-candidate-for-cytokine-immunotherapy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43003.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">413</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">2901</span> The Expression of Toll-Like Receptors Gene in Peripheral Blood Mononuclear Cells of Betong (KU Line) Chicken</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chaiwat%20Boonkaewwan">Chaiwat Boonkaewwan</a>, <a href="https://publications.waset.org/abstracts/search?q=Anutian%20Suklek"> Anutian Suklek</a>, <a href="https://publications.waset.org/abstracts/search?q=Jatuporn%20Rattanasrisomporn"> Jatuporn Rattanasrisomporn</a>, <a href="https://publications.waset.org/abstracts/search?q=Autchara%20Kayan"> Autchara Kayan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Toll-like receptors (TLR) are conserved microbial sensing receptors located on cell surface that are able to detect different pathogens. The aim of the present study is to examine the expression of TLR gene in peripheral blood mononuclear cell of Betong (KU line) chicken. Blood samples were collected from healthy 12 Betong (KU line) chicken. PBMCs were isolated and maintained in RPMI1640 with 10% FBS, penicillin and streptomycin. Cell viability was determined by trypan blue dye exclusion test. The expression of TLRs gene was investigated by polymerase chain reaction (PCR) technique. Results showed that PBMCs viability from Betong (KU line) chicken was 95.38 ± 1.06%. From the study of TLRs gene expression, results indicated that there are expressions of TLR1.1 TLR1.2 TLR2.1 TLR2.2 TLR3 TLR4 TLR5 TLR 7 TLR15 and TLR21 in PBMCs of Betong (KU line) chicken. In conclusion, PBMCs isolated from blood of Betong (KU line) chicken had a high cell viability ( > 95%). The expression of TLRs in chicken was all found in PBMCs, which indicated that PBMC isolated from the blood of Betong (KU line) chicken can be used as an in vitro immune responses study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=toll-like%20receptor" title="toll-like receptor">toll-like receptor</a>, <a href="https://publications.waset.org/abstracts/search?q=Betong%20%28KU%20line%29%20chicken" title=" Betong (KU line) chicken"> Betong (KU line) chicken</a>, <a href="https://publications.waset.org/abstracts/search?q=peripheral%20blood%20mononuclear%20cells" title=" peripheral blood mononuclear cells"> peripheral blood mononuclear cells</a> </p> <a href="https://publications.waset.org/abstracts/111706/the-expression-of-toll-like-receptors-gene-in-peripheral-blood-mononuclear-cells-of-betong-ku-line-chicken" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/111706.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">224</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">2900</span> Functional Gene Expression in Human Cells Using Linear Vectors Derived from Bacteriophage N15 Processing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kumaran%20Narayanan">Kumaran Narayanan</a>, <a href="https://publications.waset.org/abstracts/search?q=Pei-Sheng%20Liew"> Pei-Sheng Liew</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper adapts the bacteriophage N15 protelomerase enzyme to assemble linear chromosomes as vectors for gene expression in human cells. Phage N15 has the unique ability to replicate as a linear plasmid with telomeres in E. coli during its prophage stage of life-cycle. The virus-encoded protelomerase enzyme cuts its circular genome and caps its ends to form hairpin telomeres, resulting in a linear human-chromosome-like structure in E. coli. In mammalian cells, however, no enzyme with TelN-like activities has been found. In this work, we show for the first-time transfer of the protelomerase from phage into human and mouse cells and demonstrate recapitulation of its activity in these hosts. The function of this enzyme is assayed by demonstrating cleavage of its target DNA, followed by detecting telomere formation based on its resistance to recBCD enzyme digestion. We show protelomerase expression persists for at least 60 days, which indicates limited silencing of its expression. Next, we show that an intact human β-globin gene delivered on this linear chromosome accurately retains its expression in the human cellular environment for at least 60 hours, demonstrating its stability and potential as a vector. These results demonstrate that the N15 protelomerse is able to function in mammalian cells to cut and heal DNA to create telomeres, which provides a new tool for creating novel structures by DNA resolution in these hosts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chromosome" title="chromosome">chromosome</a>, <a href="https://publications.waset.org/abstracts/search?q=beta-globin" title=" beta-globin"> beta-globin</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA" title=" DNA"> DNA</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=linear%20vector" title=" linear vector"> linear vector</a> </p> <a href="https://publications.waset.org/abstracts/111231/functional-gene-expression-in-human-cells-using-linear-vectors-derived-from-bacteriophage-n15-processing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/111231.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">192</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">2899</span> Light-Controlled Gene Expression in Yeast</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peter.%20M.%20Kusen">Peter. M. Kusen</a>, <a href="https://publications.waset.org/abstracts/search?q=Georg%20Wandrey"> Georg Wandrey</a>, <a href="https://publications.waset.org/abstracts/search?q=Christopher%20Probst"> Christopher Probst</a>, <a href="https://publications.waset.org/abstracts/search?q=Dietrich%20Kohlheyer"> Dietrich Kohlheyer</a>, <a href="https://publications.waset.org/abstracts/search?q=Jochen%20Buchs"> Jochen Buchs</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorg%20Pietruszkau"> Jorg Pietruszkau</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=caged-compounds" title="caged-compounds">caged-compounds</a>, <a href="https://publications.waset.org/abstracts/search?q=gene%20expression%20regulation" title=" gene expression regulation"> gene expression regulation</a>, <a href="https://publications.waset.org/abstracts/search?q=optogenetics" title=" optogenetics"> optogenetics</a>, <a href="https://publications.waset.org/abstracts/search?q=photo-labile%20protecting%20group" title=" photo-labile protecting group"> photo-labile protecting group</a> </p> <a href="https://publications.waset.org/abstracts/50092/light-controlled-gene-expression-in-yeast" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50092.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">326</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=gene%20expression&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=gene%20expression&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=gene%20expression&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=gene%20expression&page=5">5</a></li> <li class="page-item"><a class="page-link" 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