Microarray and NGS data can be analysed (i.e., preprocessing, normalization and downstream analysis) and MD simulation run can be performed in the form of research collaboration. Interested researcher can contact us.

Network Biology

Onco-omics: Using a biological network-based approach for identification of biomarkers in complex diseases. We intend to understand the underlying biology and molecular pathogenesis of the disease, which is crucial for advancing the treatment. By doing the topological analysis of network we can find out hub genes, bottleneck genes and other conserved modules that play an important role in the disease progression. Network biology is gradually altering our view of cell biology and give a chance to understand the unforeseen internal organization of the cell.

Stem Cell Bioinformatics: To understand the underlying mechanisms of pluripotency by combining network biology and integrative bioinformatics approach. With the advent of NGS technologies large volume of transcriptomic data on regulation of pluripotency is available; however, they are scattered across wide range of databases and scientific literature. We intend to bring a consensus on how pluripotency is maintained by analyzing RNA-seq. Thus far, we have uncovered the genes those are critical for establishment and maintenance of pluripotency in human and we are working towards decoding the biology behind the two observed pluripotency stages — naive and primed.

Computational Genomics and Structural Bioinformatics

To study riboswitches (non-coding regulatory RNAs) as potential drug target using computational and structural bioinformatics approaches. The ongoing research include identification, distribution, modeling of structures and manipulation of riboswitches in some prokaryotic genomes, so that they can be identified and established as potential drug targets thus playing a pivotal role in therapeutic applications. Further, we intend to find the insights into the conformational changes and binding mechanism of riboswitch via molecular dynamics simulations and inhibitor finding for the specific riboswitch.

Evolutionary Bioinformatics

Wolbachia is a genus of gram-negative bacteria which infects arthropod species. We intend to study the evolution of genes in Wolbachia by computational phylogenetics approach. The study will help to understand the compatibility of different species of Wolbachia with their host. Reconstructing gene and species phylogenies will suggest their current existence and will help to understand the participation of those genes during speciation according to their host. We also try to identify horizontal gene transfer(HGT)/recombination events in Wolbachia using various computational methods.