Sex differences in gene expression have been widely studied in liver; these differences are primarily determined by growth hormone (GH) signaling and GH-responsive nuclear factors such as STAT5a, STAT5b and HNF4-alpha. Next Gen sequencing technologies have permitted identification of transcription factor (TF) binding sites, histone modifications, DNase hypersensitivity, transcriptional (RNA) profiles, and other markings on a genome-wide basis.
High throughput sequencing produce millions of short sequence reads and is frequently employed to the study epigenomes, transcriptomes and global transcription factor binding sites. Files containing mapped short sequences generated by high throughput sequencing are presented in the bed file format. The goal of this project is to create a database for the storage, retrieval, query and analysis of bed files.
Developed at Boston University as part of the Biological Database Analysis (BE768) course, Spring 2011, G. Benson instructor. Student developers: Quan Fang, Clark Freifeld, Christina Hao, and Andy Rampersaud. Faculty advisor: Dr. David J. Waxman.