Wednesday
21
October 2026
4:00 - 5:30 PM IST
Location
Room 201, School of Arts and Sciences
Central Campus
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Multi-Omics Technologies: From Data Generation to Biological Discovery
Arts and Sciences Lecture Series
Nisha Singh
Assistant Professor of Bioinformatics
Department of Bioinformatics
Gujarat Biotechnology University (GBU)
Speaker
The rapid advancement of high-throughput NGS technologies has transformed biological research by enabling the generation of large-scale datasets across multiple molecular and phenotypic layers, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics. Multi-omics approaches provide an integrated view of biological systems, enabling researchers to move beyond individual molecular measurements towards a comprehensive understanding of complex biological processes. However, translating massive, heterogeneous, and multidimensional datasets into meaningful biological insights remains a major challenge. We have developed and applied diverse platforms and computational approaches leveraging advances in next-generation sequencing, high-throughput genotyping such as single copy genic SNP genotyping chip for rice “OsSNPnks”, pigeonpea “CcSNPnks” and mango, “MiSNPnks” and tea haplotype map. RNA sequencing, mass spectrometry-based proteomics and metabolomics, and high-resolution phenotyping, complemented by computational workflows for quality control, data integration, statistical analysis, network biology, and AI/ML-driven discovery. Particular emphasis is placed on integrating multi-layer datasets to identify key genes, regulatory networks, metabolic pathways, biomarkers, and genomic regions associated with complex traits. Our research in crop genomics and nutritional biology, particularly in rice, pigeonpea, pearl millet, tea, and mango, demonstrates how multi-omics integration can accelerate the understanding of stress resilience, nutrient-use efficiency, nutritional quality, plant–environment interactions, and complex trait architecture. The integration of multi-omics with genome-wide association studies (GWAS), molecular breeding, functional genomics, and predictive modelling provides new opportunities to translate large-scale biological datasets into actionable knowledge for crop improvement. Furthermore, the convergence of high-throughput data generation, advanced computational biology, artificial intelligence, and experimental validation is creating a powerful framework for biological discovery. Such integrated approaches can accelerate the transition from data to knowledge, knowledge to biological mechanisms, and mechanisms to innovative solutions, with broad applications in sustainable agriculture, nutritional security, human health, and biotechnology.
Speaker
Nisha Singh
Nisha Singh is an Assistant Professor, Bioinformatics, Gujarat Biotechnology University. Professor Singh holds a PhD in Biotechnology and Bioinformatics from NIPB, New Delhi, and a Postdoc from Cornell University, New York, USA. Professor Singh also served as DST-Inspire Faculty at NIPB, New Delhi. Professor Singh's research interests lie in Genomics, Proteomics, and Bioinformatics, with a focus on developing cost-effective, high-throughput genotyping technologies for genetics and molecular breeding applications across diverse crop species, including rice, wheat, pigeonpea, and mango. These technologies will enable breeders to genotype high-throughput samples in a short time to implement genomic selection (GS) as a routine practice in breeding programs, thereby fast-tracking the development of superior crop varieties. Professor Singh developed the first patented genic 50K SNP genotyping chip, “OsSNPnks,” a single-copy gene-based chip for genetics and molecular breeding applications in rice. Similarly, fabricated 62K Pigeonpea and 80K Mango high-density SNP genotyping platforms. She worked on several international genome sequencing projects, including Wild rice, Wheat, Mango, jute, pigeon pea, and Tea. Professor Singh has developed the first Haplotype map (HapMap-1) of tea to facilitate understanding of tea genome evolution and tea metabolite pathways, thus offering effective germplasm utilisation for breeding tea varieties. Professor Singh has designed various bioinformatics databases and biological data analysis tools, including LDRGDb (Legume Disease Resistance Genes Database) and Ppomicsdb (A Multi-Omics Database for Pigeonpea Genetics and Molecular Breeding Applications). She has published +80 International research publications in reputed journals, has an h-index of +26, +2977 citations, has 3 patents, and has edited 4 books. Organised two national conferences, Biotech-2024 and Ideation 2023. For her scientific contributions, she received several prestigious awards and honours (+30), such as the INSA-Medal for Young Scientist Award-2020, the NESA-2022 Scientist of the Year Award, the NASI-Young Scientist Platinum Jubilee Award 2022, the SERB Women Excellence Award-2024, and membership in INSA-INYAS-2024. She is a Fellow of international scientific societies, Fellow of the American Society of Plant Biology (FASPB), USA, Fellow of the Linnean Society of London, UK (FLSL).