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Scientist C
y.kumar [at] thsti [dot] res [dot] in
Postdoc, Weizmann Institute of Science, Israel
PhD, National Chemical Laboratory, India
M.Sc., University of Pune

Metabolomics research has benefited significant fractions of research investigation focused on understanding, diagnosing and preventing human disease. Large number of potential biomarker has been discovered using metabolomics and many of them has been tested for translational applications.  Our research focus on discovery of new biomarker in disease condition using metabolomics, multivariate data analysis and machine learning approaches. This approach can be step forward in disease diagnostics, future prediction and prognosis for any disease condition. At present, using high-resolution mass spectrometer with tandem (MS/MS) and sequential MS/MS (MSn) capability we are trying to measure the whole set of metabolites and lipids in a diabetic condition. We work on complete pipeline from experiment design, sample preparation, analysis, data processing and bioinformatics. Additionally, we are also working on determine the structure of metabolic pathway and flux in diseased condition using stable isotope.

1. Lomate P, Dewangan V, Mahajan N, Kumar Y, Kulkarni A, Wang L, Saxsena S, Gupta VS, Giri AP. (2018) Integrated transcriptomic and proteomic analyses suggest the participation of endogenous protease inhibitors in the regulation of protease gene expression in Helicoverpa armigeraMolecular and cellular proteomics, DOI: 10.1074/mcp.RA117.000533

2. Kumar Y, Zhang L, Panigrahi P, Dholakia BB, Dewangan V, Kadoo NY, Giri AP, Tang H, Gupta VS (2016) Fusarium oxysporum mediates systems metabolic reprogramming of chickpea roots as revealed by a combination of proteomics and metabolomics. Plant Biotechnology Journal 10.1111/pbi.12522 

3. Kumar Y, Dholakia BB, Panigrahi P, Kadoo NY, Giri AP, Gupta VS (2015) Metabolic profiling of chickpea-Fusarium interaction identifies differential modulation of disease resistance pathways. Phytochemistry 116:120-129 


  1. Method to predict diabetes outcome susceptibility (Patent Application No. 201711041969, Nov. 2017)

1. Intramural grant from THSTI


1. Sonu Kumar Gupta

2. Neema Bisht

3. Vedika

4. Sonam