In our previous work, we developed four major bioinformatics tools/databases: (1) the web-based ANOVA-FDR software to provide user-friendly microarray data analysis (http://lgsun.grc.nia.nih.gov/ANOVA/); (2) an algorithm and a fully-automated computational pipeline for transcript assembly from expressed sequences aligned to the mouse genome; (3) a web-based browser to visualize all transcripts and alternative spliced forms of mouse genes (NIA Mouse Gene Index: http://lgsun.grc.nia.nih.gov/geneindex/mm9/); (4) a web-based database and tool to visualize and map the transcription factor binding sites of the mouse genome (CisView: http://lgsun.grc.nia.nih.gov/geneindex/mm6/cisview.html); and (5) a web-based tool to identify consensus sequence motifs based on the genome-wide chromatin-immunoprecipitation coupled with sequencing (ChIP-Seq) method (CisFinder: http: http://lgsun.grc.nia.nih.gov/CisFinder/). We have also developed a new algorithm to simulate the gene expression regulated by two competing transcription factors. Utilizing the bioinformatics tools developed here, we analyzed the global gene expression profiles generated after the overexpression of specific transcriptions factors in mouse ES cells. The analyses helped to identify cis-regulatory elements for both active (i.e., bound by P300, CHD7, mediator, cohesin, and SWI/SNF) or repressed (i.e., with H3K27me3 histone marks and bound by Polycomb factors) states. These results were also used to identify most likely downstream target genes for specific transcription factors. We continued to apply our software tools to various biological problems of our own and in collaboration, which yielded a few publications. We are working constantly to maintain and update the bioinformatics resources that we have developed and made available to the research community. We will continue working on the development of new algorithms and websites for bioinformatics needs. During this reporting period, we have developed a web-based software tool that allows users to carry out comprehensive analyses of gene expression profiling data by uploading their own data or downloading data from the public database, such as GEO. This webtool has been made freely available to the research community.
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