Projects

Computational Analysis of Transcriptional Regulation

People
Department of Statistics: Dr. Jing Wu and Dr. Jun Xie
Informatics School at IU Bloomington: Dr. Sun Kim and Dr. Haixu Tang
Department of Veterinary Pathobiology: Dr. Sulma I. Mohammed

Description
The regulation of gene expression plays a central role in nearly all biological processes in living cells. With many sequenced genomes and advanced genome-wide analytical technologies, it is now possible to begin constructing transcriptional regulatory networks that control gene expression in biological processes, including the process of cancer. This project focuses on the development of statistical and computational methods for the prediction of transcriptional regulatory activities, which we define as a network including information of the transcription factors (TFs), the transcription factor binding sites in non-coding genomic sequences, the genes bound by the transcription factors, and if and when the TFs occupy their binding sites. This is an interdisciplinary project involving statisticians (Drs. Wu and Xie) from the Department of Statistics at Purdue, computer scientists (Drs. Kim and Tang) from Informatics School at IU Bloomington, and an oncologist (Dr. Mohammed) from Veterinary School of Medicine at Purdue. The project is currently supported by the Collaboration in Life Scienes & Informatics Research (CLSIR) pilot grant from IU Bloomington and Purdue. A proposal to the National Institutes of Health (NIH) is pending.

Statistical and Computational Methods for Transcriptomic Profile of Drosophila Melanogaster

People
Department of Statistics: Dr. Jing Wu and Dr. Jun Xie
Department of Entomolgy: Dr. Larry Murdock and Dr. Barry Pittendrigh

Description
The rich source of gene expression microarray data contains information about co-expressed genes. However, the underlying regulatory mechanisms of these genes are mostly unknown. For many species, for instance, Drosophila fruit fly, only a small number of transcription factor binding sites are annotated (mainly embryo developmental TFs). In addition to the collections of transcription factor binding sites (TFBSs), e.g. TRANSFAC, novel TFBSs can be computationally identified in a group of co-expressed genes. This project is a collaboration between faculty in Statistics (Drs. Wu and Xie) and faculty in Entomology (Drs. Murdock and Pittendrigh) at Purdue. We are developing computational and statistical methods to identify transcriptomic profiles (a set of transcription factors regulating a set of genes) of Drosophila Melanogaster genes, especially those associated with midgut.