Profile

I am a Principal Scientist-II at THSTI, Faridabad, with a Ph.D. in Biotechnology (Computational Biology) from IGIB, which I earned in 2013. During my Ph.D., I developed MassWiz, India's first peptide identification algorithm for mass spectrometry data, and Proteome Analyst, an integrated analysis suite that was recognized by the MIT-TR35 award in 2013. Since joining THSTI in 2013, I have focused on post-translational modifications (PTMs) and big data in translational health sciences, creating innovative tools like QuantWiz-IQ, HyperQuant, and ModST for large-scale proteomics and PTMs analysis. My research interests encompass protein-protein interactions (PPIs), biological networks, and computational analysis in metabolic disoeases like NAFLD and CVDs. I have received several prestigious grants, including the DBT-IYBA, DBT-Big Data Initiative, SERB-SUPRA, and DBT-National Network Project. I am also an elected Executive Council Member of the Proteomics Society of India. My research is currently focussed on creation of a proteogenomic reference map of the human liver to study non-alcoholic fatty liver disease (NAFLD) progression.

Current Focus Areas

  • Proteogenomics and NAFLD: My primary focus is on proteogenomics, where I am leading a project to create a proteogenomic reference map of the human liver. This project aims to understand the progression of non-alcoholic fatty liver disease (NAFLD) by integrating genomics and proteomics data.

  • Computational Proteomics Tools: I am developing advanced computational tools for quantitative proteomics, including QuantWiz-IQ for iTRAQ and TMT labeling analysis, HyperQuant for high-order multiplexing, and ModST for large-scale automated identification of post-translational modifications (PTMs). These tools enable a deeper understanding of protein functions and interactions.

  • Protein-Protein Interactions (PPIs): I study protein-protein interactions (PPIs) and their roles in biological networks, focusing on how they influence health and disease. I investigate the crosstalk between PTMs and how these modifications drive protein activity, thereby affecting the evolution of biological networks over time.

Selected Publications

  • Raj, A., Aggarwal, S., Singh, P., Yadav, A. K., & Dash, D. (2024). PgxSAVy: A tool for comprehensive evaluation of variant peptide quality in proteogenomics–catching the (un) usual suspects. Computational and Structural Biotechnology Journal, 23, 711-722.

  • Aggarwal, S., Raj, A., Kumar, D., Dash, D., & Yadav, A. K. (2022). False discovery rate: the Achilles’ heel of proteogenomics. Briefings in bioinformatics, 23(5), bbac163.

  • Aggarwal, S., Banerjee, S. K., Talukdar, N. C., & Yadav, A. K. (2020). Post-translational modification crosstalk and hotspots in sirtuin interactors implicated in cardiovascular diseases. Frontiers in genetics, 11, 519883.

  • Aggarwal, S., Kumar, A., Jamwal, S., Midha, M. K., Talukdar, N. C., & Yadav, A. K. (2020). HyperQuant—a computational pipeline for higher order multiplexed quantitative proteomics. ACS omega, 5(19), 10857-10867.

  • Tolani, P., Gupta, S., Yadav, K., Aggarwal, S., & Yadav, A. K. (2021). Big data, integrative omics and network biology. Advances in protein chemistry and structural biology, 127, 127-160.

Skills & Proficiency

big data bioinformatics post-translational modifications proteogenomics proteomics multi-omics machine learning artificial intelligence metabolomics AMR metabolic disorders cardiovascular disorders PPI networks