Networks and Systems Biology
Cancer Bioinformatics: We are dedicated to identifying prognostic and diagnostic biomarkers involved in various cancer formation and progression. The sequencing of the complete human genome has brought opportunities to explore the functional and regulatory roles of yet unannotated non-coding genes. Through our bioinformatics expertise in large-scale transcriptomic data handling and network biology analysis, we are focused on exploring both coding and non-coding genes and their underlying mechanism in formation and development of Gynecological and Lung cancers. Especially we intend to unravel the shared and unique molecular mechanisms of different types of Gynecological and Lung cancer.
Stem Cell Bioinformatics: We are involved to understand the underlying mechanisms of human pluripotency by combining network biology and integrative bioinformatics approach. With the advent of NGS technologies large volume of transcriptomic data on regulation of human pluripotency is available. We intend to bring a consensus on how pluripotency is established and maintained by analyzing RNA-seq data. So far, we have uncovered the genes those are critical for establishment and maintenance of pluripotency in human, and decoded molecular markers and transcriptional circuitry of naive and primed states of human pluripotency. Further we envision to decipher the mRNA-lncRNA-miRNA interaction landscape in human pluripotency.
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.
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.