Kumar SELVARAJOO
Kumar SELVARAJOOAdjunct Associate Professor
[email protected]

Office Location – Matrix L7, Biopolis

Affiliations

Senior Principal Investigator A*STAR Bioinformatics Institute (A*STAR BII)
Adjunct Associate Professor, NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI)
Adjunct Associate Professor, School of Biological Sciences, NTU

Biography

Dr Kumar Selvarajoo is a prominent researcher in computational and systems biology. He leads the Computational Biology & Omics Laboratory at A*STAR’s Bioinformatics Institute and is an Adjunct Associate Professor at the National University of Singapore and Nanyang Technological University. Previously, he was an Associate Professor at Keio University, Japan. His expertise includes computational biology, bioinformatics, data analytics, and machine learning, with a focus on applying physical and statistical principles to complex biological systems. He has published over 90 scientific articles, authored and edited books, delivered keynote speeches at international conferences, reviewed multi-million dollar international research grants, and serves on editorial boards of multiple journals. He holds a Master’s in Aeronautics from Imperial College London and a PhD in Computational Biology from Nanyang Technological University. His contributions have advanced computational biology, systems biology and cancer research.

Professional Appointments

Associate Editor, BMC Biology, SpringerNature
Associate Editor, Frontiers in Immunology (Systems Immunology), Frontiers
Associate Editor, Genomics, Elsevier
Member, Editorial Board, Biotechnology Notes, KeAi Publishing

Education

PhD, Computational Biology, Nanyang Technological University
Meng & ACGI, Aeronautical Engineering, Imperial College of Science, Technology & Medicine

Research Interest

Systems Biology, Computational Biology, Machine Learning, Data Analytics, Cancer, Digital Twin for Biotechnology

Current Research Projects

Cancer Systems Biology, Synthetic Data, Biotechnology Applications, Multi-omics Machine Learning

Selected Publications

  1. Understanding the role of toggle genes in chronic lymphocytic leukemia proliferation. Sirbu O, Agarwal G, Giuliani A, Selvarajoo K*. NPJ Syst Biol Appl 11:91 (2025).
  2. Advancing Drug Response Prediction using Multi-modal and -omics Machine Learning Integration (MOMLIN): a Case Study on Breast Cancer Clinical Data. Rashid MM, Selvarajoo K*. Brief Bioinform. 25:4, bbae300 (2024).
  3. Identifying effective evolutionary strategies-based protocol for uncovering reaction kinetic parameters under the effect of measurement noises. Yeo HC, Vijay V, Selvarajoo K*. BMC Biology 22:235 (2024).
  4. Towards multi-omics synthetic data integration. Selvarajoo K* & Maurer-Stroh. Brief Bioinform. 25:3, bbae213, (2024).
  5. Can Digital Twin Efforts Shape Microorganisms-based Alternative Food? Helmy M, Elhalis H, Rashid MM, Selvarajoo K*. Curr Opin Biotechnol. 87:103115 (2024).
  6. Perspective: Multi-omics and Machine Learning Help Unleash the Alternative Food Potential of Microalgae. Helmy M, Elhalis H, Yan L, Chow Y, Selvarajoo K*. Adv Nutr., 14:1-11 (2023).
  7. The transformation of our food system using cellular agriculture: What lies ahead and who will lead it? Smith DJ, Helmy M, Lindley ND, Selvarajoo K*. Trends Food Sci Technol, 127:368-376 (2022).
  8. Identifying toggle genes from transcriptome-wide scatter: A new perspective for biological regulation. Guiliani A*, Bui TT, Helmy M, Selvarajoo K*. Genomics, 114:215-228 (2022).
  9. A Systems Biology Approach to Suppress TNF-induced Proinflammatory Gene Expressions. Hayashi K, Piras V, Tabata S, Tomita M & Selvarajoo K* Cell Commun. Signal., 11:84 (2013).
  10. Physical Laws Shape Biology. Selvarajoo K* & Tomita M Science 339:646 (2013).

* Corresponding author; # Co-first author