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100			_aMahima V S (93514007) _98202
245			_aConstruction and analysis of regulatory networks in breast cancer
502			_bMaster of Philosophy in Computer Science _c2014-2015 _dEXT _eElizabeth Sherly _fUmesh P (Dept. of Computational Biology and Bioinformatics ) _g"Dept. of Computational Biology and Bioinformatics University of Kerala"
520			_aBreast cancer is a complex and heterogeneous disease having different pathological conditions. Identification of genes associated with breast cancer provides helpful information which can be used for providing better treatment and personalized medicines.Numerous methodologies are now available to examine the genes regulated by breast cancer. Recent advances in Bioinformatics have enabled to analyze the data obtained from various sources such as microarray, ChIP-Seq, RNA-Seq etc. Analyses of the differential expression obtained from RNA-Seq data provide useful information for the construction and analysis of biological networks. For this work, six RNA-Seq control cell lines data obtained from NCBI (a public repository) have been analyzed to obtain the differential expression using the standard RNA-seq pipeline. GFold is used to get the rank of differentially expressed genes. Common up-regulated and down-regulated genes in all the cell lines and uniquely regulated genes in each cell line has been annotated using DAVID and WebGestalt for biological interpretations. Inferring of KEGG pathway and gene ontologies of regulated genes (up and down) gives some interesting results. Regulation of action cytoskeleton, MAPK signaling, wnt signaling, VEGF signaling pathway, cell adhesion molecules are the pathways significantly over represented in up-regulated genes. Cytokine-cytokine receptor interaction, Neuroactive ligand-receptor interaction are the pathways significantly associated with down-regulated genes.
650			_aTHEORY OF COMPUTATION _98203
650			_aDYNAMIC PROGRAMMING _98204
650			_aREGULATORY NETWORKS _98205
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