Research

Our research includes developing software as well as applying statistical machine learning, bio-molecular simulation and information retrieval to analyse and mine all kinds of biological data, including nucleotide sequences, protein sequences and structures, microarray as well as next generation sequencing (NGS) data for the purpose of facilitating biology discovery.

Our research areas focus on a variety of topics but basic themes includes Evolution, Comparative Genomics, System biology as well as Functional Genomics.

Within this field We are focusing on the major topics:

Evolution of Immune System in plants

STAND P-loop NTPase is the common weapon used by plant and other organisms from all three kingdoms of life to defend themselves against pathogen invasion. The purpose of this study is to review comprehensively the latest finding of plant STAND P-loop NTPase related to their genomic distribution, evolution, and their mechanism of action. Earlier, the plant STAND P-loop NTPase known to be comprised of only NBS–LRRs/AP–ATPase/NB–ARC ATPase. However, recent finding suggests that genome of early green plants comprised of two types of STAND P-loop NTPases: (1) mammalian NACHT NTPases and (2) NBS–LRRs. STAND P-loop NTPase is the common weapon used by plant and other organisms from all three kingdoms of life to defend themselves against pathogen invasion.. Earlier, the plant STAND P-loop NTPase known to be comprised of only NBS–LRRs/AP–ATPase/NB–ARC ATPase. However, our recent finding suggests that genome of early green plants comprised of two types of STAND P-loop NTPases: (1) mammalian NACHT NTPases and (2) NBS–LRRs. (Molecular Genetics & Genomics, 2018; PloS One, 2016)

Machine learning & system biology approaches for genome-wide investigation of disease resistance in Plants

Nucleotide binding site leucine-rich repeats (NBS-LRR) disease resistance proteins play an important role in plant defense against pathogen attack. A number of recent studies have been carried out to identify and characterize NBS-LRR gene families in many important plant species. In this study, we identified NBS-LRR gene family comprising of 1015 NBS-LRRs using highly stringent computational methods. These NBS-LRRs were characterized on the basis of conserved protein motifs, gene duplication events, chromosomal locations, phylogenetic relationships and digital gene expression analysis. Surprisingly, equal distribution of Toll/interleukin-1 receptor (TIR) and coiled coil (CC) (1∶1) was detected in apple while the unequal distribution was reported in majority of all other known plant genome studies. Prediction of gene duplication events intriguingly revealed that not only tandem duplication but also segmental duplication may equally be responsible for the expansion of the apple NBS-LRR gene family (Plos One, 2014)

Artificial intelligence approaches for Drug Discovery from Himalayas

Major challenges in the cancer research include the prioritization of targets and also the identification of novel smallmolecules that could inhibit the drug targets. Considering both aspects simultaneously, herein, an integrated computational pipeline has been established which links prioritized oral cancer drug targets with the identification of small molecule inhibitors of plant origin. The system-level approach that we have presented for OSCC may allow researchers to analyze large volumes of data and discover new potential drug targets in other complex human diseases. We expect that the three potential PDMs identified for CXCR4 can be ideal for experimental studies as potential novel anti-oral cancer agents. The lead molecules reported herein may also provide better insights for designing potential CXCR4 inhibitors with improved efficacy and fewer side effects. (BMC Medical Genomics, 2015; Molecular BioSystems, 2015)

Genomic and evolutionary insights into the cold adaptation enzymes of microbes isolated from Himalayas

The complete genome sequence of Janthinobacterium lividum ERGS5:01 isolated from from Sikkim Himalaya was performed owing to understand its survival at aquatic ecosystem at high elevation. Our Next generation sequencing platform was carried out using PacBio RSII sequencing with generated genome of ~5.1 MB with 4575 protein-coding genes and 118 RNA genes. Furthermore, the genome comparisons across genus 20 different psychotolerants Janthinobacterium revealed an open pan-genome with high genomic diversity Extended insight into the genome provided clues of crucial genes associated with adaptation in the harsh aquatic ecosystem of high altitude. This strain ERGS5:01 will helped us understanding the role of its survival mechanism in harsh high altitude aquatic environment and to obtain insight into bioprospection opportunities utilizing industrial enzymes. Additionally, present study involving comparative genomics provided intriguing facts on genomic diversity among strains in the genus Janthinobacterium besides revealing important gene clusters responsible for cold adaptation (Genomics, 2018; Standards in Genomic Sciences, 2018)