Gourab Das

Sanjeevani is a curated anti-cancer phytochemical database with predictive models and tools for molecular docking and pharmacokinetics, achieving high accuracy in classification and docking performance.

The paper develops a machine learning method to identify gene-physiological response associations using literature data from bacterial and plant species.

The paper develops a method to identify stress-associated genes in rice using DNA repeat probes and applies it to 9 Oryza species and other plants.

LitRev identifies common and important biological phrases from PubMed to aid in quick literature reviews.

The paper benchmarks DNA repeat identification tools across diverse genomes, finding consistency in perfect microsatellite detection but variability in long and imperfect repeat identification.