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Full-Text Articles in Life Sciences
Dprp: A Database Of Phenotype-Specific Regulatory Programs Derived From Transcription Factor Binding Data, David T. W. Tzeng, Yu-Ting Tseng, Matthew Ung, I-En Liao, Chun-Chi Liu, Chao Cheng
Dprp: A Database Of Phenotype-Specific Regulatory Programs Derived From Transcription Factor Binding Data, David T. W. Tzeng, Yu-Ting Tseng, Matthew Ung, I-En Liao, Chun-Chi Liu, Chao Cheng
Dartmouth Scholarship
Gene expression profiling has been extensively used in the past decades, resulting in an enormous amount of expression data available in public databases. These data sets are informative in elucidating transcriptional regulation of genes underlying various biological and clinical conditions. However, it is usually difficult to identify transcription factors (TFs) responsible for gene expression changes directly from their own expression, as TF activity is often regulated at the posttranscriptional level. In recent years, technical advances have made it possible to systematically determine the target genes of TFs by ChIP-seq experiments. To identify the regulatory programs underlying gene expression profiles, we …
Orthoclust: An Orthology-Based Network Framework For Clustering Data Across Multiple Species, Koon-Kiu Yan, Daifeng Wang, Joel Rozowsky, Henry Zheng, Chao Cheng, Mark Gerstein Gerstein
Orthoclust: An Orthology-Based Network Framework For Clustering Data Across Multiple Species, Koon-Kiu Yan, Daifeng Wang, Joel Rozowsky, Henry Zheng, Chao Cheng, Mark Gerstein Gerstein
Dartmouth Scholarship
Increasingly, high-dimensional genomics data are becoming available for many organisms.Here, we develop OrthoClust for simultaneously clustering data across multiple species. OrthoClust is a computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific. We demonstrate the application of OrthoClust using the RNA-Seq expression profiles of Caenorhabditis elegans and Drosophila melanogaster from the modENCODE consortium. A potential application of cross-species modules is to infer putative analogous functions of uncharacterized elements like non-coding RNAs based on guilt-by-association.
Functional Genomics Annotation Of A Statistical Epistasis Network Associated With Bladder Cancer Susceptibility, Ting Hu, Qinxin Pan, Angeline S. Andrew, Jillian M. Langer, Michael D. Cole, Craig R. Tomlinson, Margaret R. Karagas, Jason H. Moore
Functional Genomics Annotation Of A Statistical Epistasis Network Associated With Bladder Cancer Susceptibility, Ting Hu, Qinxin Pan, Angeline S. Andrew, Jillian M. Langer, Michael D. Cole, Craig R. Tomlinson, Margaret R. Karagas, Jason H. Moore
Dartmouth Scholarship
Background: Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility. …