INTEGRATIVE SYSTEM BIOLOGY STUDIES ON HIGH THROUGHPUT GENOMICS AND PROTEOMICS DATASET

Abstract

The post genomic era has propelled us to the view that the biological systems are complex network of interacting genes, proteins and small molecules that give rise to biological form and function. The past decade has seen the advent of number of new technologies designed to study the biological systems on a genome wide scale. These new technologies offers an insight in to the activity of thousands of genes and proteins in cell thereby changed the conventional reductionist view of the systems. However the deluge of data surpasses the analytical and critical abilities of the researches and thereby demands the development of new computational methods. The challenge no longer lies in the acquisition of expression profiles, but rather in the interpretation for the results to gain insights into biological mechanisms. In three different case studies, we applied various system biology techniques on publicly available and in-house genomics and proteomics data set to identify sub-network signatures. In First study, we integrated prior knowledge from gene signatures, GSEA and gene/protein network modeling to identify pathways involved in colorectal cancer, while in second, we identified plasma based network signatures for Alzheimer's disease by combining various feature selection and classification approach. In final study, we did an integrated miRNA-mRNA analysis to identify the role of Myeloid Derived Stem Cells (MDSCs) in T-Cell suppression.