Funding Agency: GLA University, Mathura
Title of the project: Computational System Genetic-approaches to identify key Molecular players of Cellular physiology, and complex traits (Ongoing)
Principal Investigator: Dr. Aditya Saxena
Project Cost- 5, 50,000/-
Project Duration- 2 Years
Abstract
Availability of high throughput genomics, proteomics, and metabolomics data accompanied with the advances in computational methodologies has ushered the way toward system genetics at molecular level that promises to unravel molecular causes of complex biological interactions in between microbes and macrobes (both plants and animals) unrevealing novel drug targets. We would like to explore the interactions in between the genome, metabolome to develop a better understanding of the causes leading to metabolic disorders (type 2 diabetes, cancer etc) as well as changes that occurs during embryonic development, cell differentiation and apoptosis.
All biological phenomena's are indeed the result of complex interplay between genetic-, epigenetic-, environmental- as well as life style-related factors and therefore do not follow the mandalian pattern of inheritance.
In order to reconstruct statistically-principled system genetic-models for these biological phenomenon using genome-scale omics data, it is imperative to dispose adequate computational power.
Present research study is designed to undertake a plethora of bioinformatics investigations viz. DNA microarray, RNA-seq, ChIP-seq, in-silico docking, etc. of relevant data to reconstruct integrative models of these complex diseases.
We are mainly focusing on computational methods available via. Two extensively used open source software tools: Cytoscape and R-based Bioconductor. These tools are in wide use due to the ease of implementation of state-of-art statistical methods, as well as -omics data analysis and integration.