I am an Assistant Professor in the Department of Data Science, Centre of Biomedical Research, SGPGIMS, campus, Lucknow India. My Lab is focusing on the following areas.

Leveraging AI algorithms and OMICS analysis for in-silico drug discovery and predictive identification of diagnostic biomarkers for early disease diagnosis.

1. Biological Data Mining: Proficient in extracting meaningful patterns and insights from complex biological datasets, including OMICS data (such as single-cell sequencing, RNA bulk, WGS, WES, proteomics, transcriptomics, and metagenomics).

2. In-Silico Drug Discovery: Skilled in utilizing computational methods and algorithms to identify potential drug candidates, conduct virtual screening, predict drug-target interactions, and assess pharmacokinetic properties.
3. AI and Machine Learning Algorithms for Diagnostic Biomarker Discovery: Experienced in developing and applying AI and ML techniques to analyze biomedical data for the discovery of diagnostic biomarkers. Capable of leveraging advanced algorithms to improve patient care through early disease detection.
4. Tumor Microenvironment and T Cell Plasticity: Specialized in studying the intricate interactions within the tumor microenvironment and the plasticity of T cells. Proficient in predicting responses to immunotherapy and chemotherapy and identifying novel biomarkers for disease diagnosis and treatment prognosis.
5. Mathematical Modeling for Disease Mechanisms: Proficient in mathematical modeling techniques, particularly using machine learning approaches, to gain insights into disease mechanisms. Skilled in building predictive models to understand disease progression and identify potential therapeutic targets.
6. Computational Drug Design and Repurposing: Demonstrated expertise in computational drug design, including structure-based and ligand-based approaches. Experienced in repurposing existing drugs for new indications through computational screening and analysis.
7. In-Silico Pharmacokinetic Studies: Experienced in conducting pharmacokinetic studies using computational models to predict drug absorption, distribution, metabolism, and excretion (ADME) properties. Skilled in optimizing drug dosing regimens and assessing drug safety profiles.

• Research

  Our research at the Department of Data Sciences, Centre of BioMedical Research, SGPGIMS, Lucknow, focuses on Medical Data Sciences. We specialize in developing and deploying computational methods, algorithms, Machine Learning, and OMICS technologies to enhance our understanding of diseases. Our primary goals include identifying biomarkers for early disease diagnosis, repurposing drugs to improve patient treatment, and ultimately reducing the burden on hospitals. By leveraging these approaches, we aim to advance healthcare by optimizing clinical outcomes and patient care.

Research publications

1. Artificial Intelligence, Deep Learning and Precision Medicine
2. Short-term dietary changes can result in mucosal and systemic immune depression
3. Comparative sequence analysis of SARS nCoV and SARS CoV genomes for variation in structural proteins
4. Fatty acid-binding protein-4 (FABP4) and matrix metalloproteinase-9 (MMP9) as predictive values for nonalcoholic steatohepatitis (NASH)
5. Computational investigation of natural compounds as potential main protease (Mpro) inhibitors for SARS-CoV-2 virus
6. The impact of CD4+ T cell plasticity in colorectal cancer on immunotherapeutic strategies
7. Broad-Spectrum Inhibitors against Class A, B, and C Type β-Lactamases to Block the Hydrolysis against Antibiotics: Kinetics and Structural Characterization
8. Current potential therapeutic approaches against SARS-CoV-2: a review
9. Synthesis and bioactivity evaluation of eugenol hybrids obtained by Mannich and 1, 3 dipolar cycloaddition reactions
10. Synthesis, molecular modelling studies of indolyl chalcone derivatives and their antimalarial activity evaluation
11. Design, Synthesis, Characterization and In Silico Molecular Docking Studies and In Vivo Anti-inflammatory Activity of Pyrazoline Clubbed Thiazolinone Derivatives
12. An improved synthesis of indanocine and antiproliferative activity of 2‐benzylindanocine via microtubule destabilization
13. Bioinformatics and computational tools in bioremediation and biodegradation of environmental pollutants
14. Application of omics technologies for microbial community structure and function analysis in contaminated environment
15. Silymarin, a polyphenolic flavonoid impede Plasmodium falciparum growth through interaction with heme
16. In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing
17. In silico identification and docking-based drug repurposing against the main protease of SARS-CoV-2, causative agent of COVID-19
18. Antiproliferative activity of diarylnaphthylpyrrolidine derivative via dual target inhibition
19. Brevifoliol ester induces apoptosis in prostate cancer cells by activation of caspase pathway
20. Bivalent furostene carbamates as antiproliferative and antiinflammatory agents
21. 3‐Arylindanones and related compounds as antiproliferative agents against colorectal cancer
22. Tools and Methods in the Analysis of Simple Sequences
23. Genome-wide detection of terpene synthase genes in holy basil (Ocimum sanctum L.)
24. AromaDb: a database of medicinal and aromatic plant’s aroma molecules with phytochemistry and therapeutic potentials
25. Detection of aroma compound’s binding mode conformations on anticancer target DNA topoisomerase II
26. Design and synthesis of novel oleanolic acid based chromenes as anti-proliferative and anti-inflammatory agents
27. Antimalarial activity and safety assessment of Flueggea virosa leaves and its major constituent with special emphasis on their mode of action
28. In vitro antimalarial activity and molecular modeling studies of novel artemisinin derivatives