• Computational Biology and Omics Group

    Bioinformatics Institute (BII), A*STAR

    Singapore Institute of Food and Biotechnology Innovation (SIFBI), A*STAR

    Recent Highlights

Welcome to The Computational Biology and Omics Group|SIFBI|A*STAR

Who We Are

The Computational Biology and Omics group performs a number of cutting-edge analyses to interpret the complex, dynamic and large-scale datasets obtained from time-series transcriptomics, proteomics and metabolomics. The members of our group comes with diverse mathematical, computational and statistical expertise with wide international exposure.
Depending on the type of data, the team develops a number of custom-made computational, mathematical and data analytic tools to investigate and predict an optimal outcome of a desired experiment. For example, for the optimal production of an industrially relevant compound, the models developed can test numerous targets in silico and identify/rank the best targets before actual experiments are performed. This reduces laborious experiments, thereby, saving valuable time and cost for projects.

SYSTEMS
BIOLOGY



Omics DATA
ANALYSIS



MATHEMATICAL
MODELING



Group Members

Kumar Selvarajoo, PhD

Group Head
Computational Biology and Omics Group

Biography
Kumar is heading the Computational Biology & Omics division at SIFBI, A*STAR. He is also an adjunct Principal Investigator at the Synthetic Biology center (SynCTI), National University of Singapore. Prior, he was an Associate Professor in Systems Biology at the Institute for Advanced Biosciences, Keio University, Japan. He serves the editorial board of Genomics (Elsevier) and Scientific Reports (Nature Publishing Group). He has lead teams in Computational Biology, Systems Biology, Bioinformatics and Statistical Genetics. In particular, he has used original ideas, utilizing fundamental statistical laws, to investigate multi-dimensional datasets, deterministic and stochastic modelling of complex signaling and metabolic networks. He has authored over 60 scientific articles, largely as corresponding author, which includes a single-authored book on Immuno Systems Biology (Springer). He has obtained several research grants, and has been an international grant reviewer. He has also presented invited/keynote talks at numerous international conferences. In 2013, 2015 and 2018, he founded and chaired the Symposium on Complex Biodynamics and Networks (cBio).

Research Interests: Computational Biology, Systems Biology, Bioinformatics and Statistical Genetics


Derek Smith, Phil

Research Scientist
Computational Biology and Omics Group

Biography
Derek obtained his B.Sc and D.Phil. in Chemistry at the University of York, UK. He has been working in Singapore for 15 years, and spent 4 years with Codexis, a US-based biotechnology company. In 2015, he moved from A*STAR’s Bioinformatics Institute (BII) to join a growing lab that would eventually become part of the Singapore Institute of Food and Biotechnology Innovation (SIFBI). He is interested in bioinformatics, protein modelling, protein engineering and directed evolution, as well as elucidating novel biosynthetic pathways to compounds of commercial relevance.

Research Interests: Protein Modelling and Engineering, Directed Evolution, Biosynthetic Pathway Design


Mohamed Helmy, PhD

Senior Bioinformatics Specialist
Computational Biology and Omics Group

Biography
Mohamed received his BSc degree in Genetics from Al-Azhar University (Cairo, Egypt), a postgraduate diploma in Software Systems Development from the Information Technology Institute (Giza, Egypt) and MSc and PhD degrees in System Biology from Keio University (Tokyo, Japan). He did his postdoctoral training at the School of Pharmaceutical Sciences at Kyoto University (Kyoto, Japan) and the School of Medicine at the University of Toronto (Toronto, Canada). He I led the bioinformatics team at BenchSci.com, the artificial intelligence-aided search engine for scientific reagents, before joining A*STAR as a Senior Bioinformatics Specialist. He participated in several international collaboration projects including the Pan Cancer Analysis of Whole Genomes (PCAWG) (Nature, 2020, 578 (7793), 82) and the Human Reference Protein Interactome Mapping Project (HuRI) (Nature, 2020, 580 (7803). He helped in building BenchSci.com to be one of the most successful biotech startups worldwide.

Research Interests
Systems Biology, Computational Biology, Proteogenomics, Metabolomics, Personalized Medicine


Jasmeet Kaur Khanijou, PhD

Research Fellow
Computational Biology and Omics Group

Biography
Jasmeet obtained her BSc in Chemistry from the National University of Singapore (NUS, Singapore). After obtaining her MSc in Forensic Science from King’s College London (UK), she helped to develop methods on analytical instruments for the analysis of compounds such as explosives, pesticides, and narcotics for border security in Singapore. She received her PhD in Chemistry from NUS, Singapore where she traced protein turnover using mass spectrometry to study protein ageing in an animal model. This has heightened her interest in studying fluxes and she would like to learn more on developing mathematical models to better understand these fluxes.

Research Interests
Analytical Chemistry, Proteomics, Metabolomics, Systems Biology


Thuy Tien Bui, BSc

Research Officer
Computational Biology and Omics Group

Biography
Thuytien obtained her B.Eng in Bioengineering at Nanyang Technological University, Singapore. In 2018, she joined a growing lab that would eventually become part of the Singapore Institute of Food and Biotechnology Innovation (SIFBI) A*STAR. She is interested in computational biology and high-dimensional data analysis, as well as the application of artificial intelligence in genetics and genomics.

Research Interests:Computational Biology, High-Dimensional Data Analysis, Artificial Intelligence, Genomics


Biostatistical Tools

ABioTrans is a software tool that identifies gene expression variability through entropy and noise analyses. It is focused on commonly-used statistical techniques, namely, Pearson and Spearman rank correlations, Principal Component Analysis (PCA), k-means and hierarchical clustering, Shannon entropy, noise (square of coefficient of variation), differential expression (DE) analysis, and gene ontology classifications.


GeneCloudOmics is a web-based bio-statistical/informatics tool developed in R for gene expression analysis.
GeneCloudOmics allows the user to directly read RNA-Seq or Microarray data files, pre-process them and perform several statistical and data mining analyses. It provides easy options for multiple statistical distribution fitting, Pearson and Spearman rank correlations, PCA, k-means and hierarchical clustering, differential expression (DE) analysis, Shannon entropy and noise (square of the coefficient of variation) analyses, Entropy analysis, support vector machine (SVM) and Random Forest clustering, tSNE and SOM analyses.
GeneCloudOmics also provides several gene and protein datasets analyses such as gene ontology (GO) classifications, pathways enrichment, protein-protein interaction (PPI), subcellular localization, protein complex enrichment, protein domains annotation and Protein Sequence Download.

Recent Highlights

Recent Highlights


  • Kumar Selvarajoo provided a talk on entitled "Computational Approaches for Understanding the Complexity of Biofilm Response" in the SCELSE virtual seminar, Nanyang Technological University, Singapore, on May 5, 2021
  • Derek Smith recently gave a talk on the 22nd Sept, 2020, entitled ‘Engineered Biosynthetic Routes to Food Additives and Flavours’ to the National University of Singapore (NUS) student group ‘Vision of Equality for a Greener Earth’ (VEGE)
  • Kumar Selvarajoo provided a talk on “Systems Biology for Agritech & Food Biotechnology” at the Virtual Showcase: Postgraduate Careers in Agri-Tech / Agri-Food Sectors, Sept 14-18, 2020 organized by the National University of Singapore:
  • Mohamed Helmy’s and Kumar Selvarajoo’s eLetter, “Exploring Artificial Intelligence for the Future of Food Security” published in Science


Recent Submitted Manuscripts


  1. Smith, Derek Helmy, Mohamed Lindley, Nicholas D. & Selvarajoo, Kumar . The Transformation of Our Food System using Lab-Grown Meat: What Lies Ahead and Who Will Lead It?
  2. Helmy, Mohamed, Agrawal, Rahul, Soudy, Mohamed, Bui, Thuy Tien, Selvarajoo, Kumar. GeneCloudOmics: A Data Analytic Cloud Platform for High-throughput Gene Expression Analysis and Visualization.

Recent Publications (Last 5 years)


  1. Selvarajoo, Kumar. "Searching for unifying laws of general adaptation syndrome. Comment on" Dynamic and thermodynamic models of adaptation" by Gorban et al." Physics of Life Reviews 37 (2021): 97-99.
  2. Helmy, Mohamed, Smith Derek, Selvarajoo Kumar. Systems biology approaches integrated with artificial intelligence for optimized food-focused metabolic engineering. Metabolic Engineering Communications, e00149.
  3. Bui, Thuy Tien, Lee Daniel, Selvarajoo Kumar. ScatLay: Utilizing Transcriptome-wide Noise for Identifying and Visualizing Differentially Expressed Genes. Scientific reports 10 (1), 1-11 2020 .
  4. Selvarajoo Kumar. Systems Biology Approaches for Understanding Biofilm Response. In Quorum Sensing - Microbial Rules of Life, Dhiman S (editor) ACS Publications, Washington (2020).
  5. Bui, Thuy Tien, and Kumar Selvarajoo. "Attractor concepts to evaluate the transcriptome-wide Dynamics Guiding Anaerobic to Aerobic State transition in Escherichia coli." Scientific reports 10.1 (2020): 1-14.
  6. Luck, Katja, et al. "A reference map of the human binary protein interactome." Nature 580.7803 (2020): 402-408.
  7. Bailey, Matthew H., et al. "Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples." Nature communications 11.1 (2020): 4748.
  8. Rheinbay, Esther, et al. "Analyses of non-coding somatic drivers in 2,658 cancer whole genomes." Nature 578.7793 (2020): 102-111.
  9. The, I. C. G. C., TCGA Pan-Cancer Analysis of Whole, and Genomes Consortium. "Pan-cancer analysis of whole genomes." Nature 578.7793 (2020): 82.
  10. Paczkowska, Marta, et al. "Integrative pathway enrichment analysis of multivariate omics data." Nature communications 11.1 (2020): 1-16.
  11. Reyna, Matthew A., et al. "Pathway and network analysis of more than 2500 whole cancer genomes." Nature communications 11.1 (2020): 1-17.
  12. Bailey, Matthew H., et al. "Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples." Nature Communications 11.1 (2020): 1-27.
  13. Shuai, Shimin, Steven Gallinger, and Lincoln Stein. "Combined burden and functional impact tests for cancer driver discovery using DriverPower." Nature communications 11.1 (2020): 1-12.
  14. Carlevaro-Fita, Joana, et al. "Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis." Communications biology 3.1 (2020): 1-16.
  15. Deveaux, William, and Kumar Selvarajoo. "Searching for simple rules in Pseudomonas aeruginosa biofilm formation." BMC research notes 12.1 (2019): 763.
  16. Selvarajoo, Kumar. "Large-scale-free network organisation is likely key for biofilm phase transition." Engineering Biology 3.4 (2019): 67-71.
  17. Deveaux, William, Kentaro Hayashi, and Kumar Selvarajoo. "Defining rules for cancer cell proliferation in TRAIL stimulation." NPJ systems biology and applications 5.1 (2019): 1-8.
  18. Yutong, Zou, Bui Thuy Tien, and Kumar Selvarajoo. "ABioTrans: A Biostatistical tool for Transcriptomics Analysis." bioRxiv (2019): 616300.
  19. Piras, Vincent, Adam Chiow, and Kumar Selvarajoo. "Long-range order and short-range disorder in Saccharomyces cerevisiae biofilm." Engineering Biology 3.1 (2019): 12-19.
  20. Selvarajoo, Kumar. "Variability that causes collective behavior." Organisms. Journal of Biological Sciences 3.1 (2019): 15.
  21. Tien, Bui Thuy, Alessandro Giuliani, and Kumar Selvarajoo. "Statistical Distribution as a Way for Lower Gene Expressions Threshold Cutoff." Organisms. Journal of Biological Sciences 2.2 (2018): 55-58.
  22. Selvarajoo, Kumar. "Order parameter in bacterial biofilm adaptive response." Frontiers in microbiology 9 (2018): 1721.
  23. Selvarajoo, Kumar. "Complexity of biochemical and genetic responses reduced using simple theoretical models." Systems Biology. Humana Press, New York, NY, 2018. 171-201.
  24. Selvarajoo, Kumar, Vincent Piras, and Alessandro Giuliani. "Hints from information theory for analyzing dynamic and high-dimensional biological data." Systems Biology. Springer, Cham, 2018. 313-336.
  25. Bong, Yong Koy, et al. "Baeyer–Villiger monooxygenase-mediated synthesis of esomeprazole as an alternative for kagan sulfoxidation." The Journal of organic chemistry 83.14 (2018): 7453-7458.
  26. Xu, Feng, et al. "Synthesis of vibegron enabled by a ketoreductase rationally designed for high pH dynamic kinetic reduction." Angewandte Chemie 130.23 (2018): 6979-6983.
  27. Soliman, Sameh, et al. "Understanding the phytohormones biosynthetic pathways for developing engineered environmental stress-tolerant crops." Biotechnologies of Crop Improvement, Volume 2. Springer, Cham, 2018. 417-450.
  28. Tong, Jiefei, et al. "Integrated analysis of proteome, phosphotyrosine‐proteome, tyrosine‐kinome, and tyrosine‐phosphatome in acute myeloid leukemia." Proteomics 17.6 (2017): 1600361.
  29. Yeo, W. L., et al. "Probing the molecular determinants of fluorinase specificity." Chemical Communications 53.17 (2017): 2559-2562.
  30. Selvarajoo, Kumar. "A systems biology approach to overcome TRAIL resistance in cancer treatment." Progress in Biophysics and Molecular Biology 128 (2017): 142-154.
  31. Sun, Huihua, et al. "Directed Evolution of a Fluorinase for Improved Fluorination Efficiency with a Non‐native Substrate." Angewandte Chemie 128.46 (2016): 14489-14492.
  32. Helmy, Mohamed, Alexander Crits-Christoph, and Gary D. Bader. "Ten simple rules for developing public biological databases." (2016): e1005128.
  33. Selvarajoo, Kumar. "Can the second law of thermodynamics hold in cell cultures?." Frontiers in Genetics 6 (2015): 262.
  34. Simeoni, Oriane, et al. "Tracking global gene expression responses in T cell differentiation." Gene 569.2 (2015): 259-266.
  35. Piras, Vincent, and Kumar Selvarajoo. "The reduction of gene expression variability from single cells to populations follows simple statistical laws." Genomics 105.3 (2015): 137-144.
  36. Selvarajoo, Kumar. "Measuring merit: take the risk." Science 347.6218 (2015): 139-140.
  37. Hayashi, Kentaro, et al. "Systems biology strategy reveals PKCδ is key for sensitizing TRAIL-resistant human fibrosarcoma." Frontiers in Immunology 5 (2015): 659.
  38. Selvarajoo, Kumar. "Conceptualising Cell Signaling and Transcriptome-wide Response for Targeted Experimentations." KEIO SFC Journal vol.15 (2015) No.1
  39. Selvarajoo Kumar. “Microscopic and Macroscopic Insights of Dynamic Cell Behavior”. In The Future of Scientific Practice: ‘Bio-Techno-Logos’, Bertolaso M (editor) Pickering & Chatto, London, (2015) pp.13-29.

Contact Us


Address: 61 Biopolis Drive, #04-14, Singapore 138673

Tel: +65 8284-7768

Email: kumar_selvarajoo@sifbi.a-star.edu.sg