2026

Yeo HC, Selvarajoo K (2026) Are we ready for causal discoveries in biological systems using deep learning? Brief Bioinform. 27(2) bbag127. https://doi.org/10.1093/bib/bbag127.

Helmy M,  Selvarajoo K (2026) Systems Biology in the Era of AI: "Winter" or "Evolution"? Front. Syst. Biol. 6:1818525. https://doi.org/10.3389/fsysb.2026.1818525.

Helmy M, Shafei F, Pellegrina D, Lingling  J, Alhossary AA, Wilson HL, Mansour T, Selvarajoo K (2026) AI-Driven Discovery in Protein Science for Immunology and Infectious Disease Research. Front. Bioinform. 6:1760257. https://doi.org/10.3389/fbinf.2026.1760257.

Pabis K, Wang W, Selvarajoo K, Budovskaya YV, Sorrentino V, Gruber J, Kennedy BK (2006) Supplements and Drugs Are Associated With Biological Age in a Cohort of Exceptionally Healthy Individuals. Aging Cell. 25(6):e70517. https://doi.org/10.1111/acel.70517.

Unfried M, Huai W, Pabis K, Jose S, Lim ZM, Alon U, Cvijovic M, Eynon N, Fedichev P, Kim Y, Whye LK, Kerepesi C, Koh WP, Kriukov D, Kaeberlein M, Ling F, Pridham G, Rera M, Rulands S, Rutenberg A, Selvarajoo K, Shenhar B, Scheibye-Knudsen M, Tarkhov AE, Teschendorff A, Wang W, Yong EH, Yang Y, Gruber J, Kennedy BK. Foundations of Gerophysics (2026) Aging (Albany NY) 18(1):513-530. https://doi.org/10.18632/aging.206378.

Rashid MM,  Low BH, Selvarajoo K  (2026) Platform Biological Divergence: quantifying gene-level differences between bulk and single-cell transcriptomics in breast cancer. bioRxiv 2026.01.22.700982. https://doi.org/10.64898/2026.01.22.700982

Zhang S, Selvarajoo K (2026) Synthetic Data to Explore Transcriptional Regulation of Differentially Expressed Genes in Ovarian Cancer. bioRxiv 2026.01.15.699618. https://doi.org/10.64898/2026.01.15.699618

2025

Mainali P, Khongsaya N, Shang B, Au-Yeung Y, Congqiang Z, Selvarajoo K, Chow Y, Poh CL (2025) Kinetic Modeling of Terpenoid Production in E.coli: Insights into Subpopulation Emergence and Process Optimisation. Microb. Cell Fact. 25(1):30. https://doi.org/10.1186/s12934-025-02895-7

Helmy M, Jin L, Alhossary A, Mansour T, Pellagrina D, Selvarajoo K (2025) Ten Simple Rules for Optimal and Careful use of Generative AI in Science. PLoS Comput Biol 21(10): e1013588. https://doi.org/10.1371/journal.pcbi.1013588 

Low BH, Rashid MM, Selvarajoo K  (2025) Machine Learning Differentiates Between Bulk and Pseudo-bulk RNA-seq in Ovarian Cancer. bioRxiv 2025.07.01.661895; doi: https://doi.org/10.1101/2025.06.27.661895

Sirbu O, Agarwal G, Giuliani A, Selvarajoo K (2025) Understanding the Role of Toggle Genes in Chronic Lymphocytic Leukemia Proliferation. NPJ Syst Biol Appl. doi: https://doi.org/10.1038/s41540-025-00575-1

Yusof Z, Tong YW, Selvarajoo K, Parakh SK, Foo SC (2025). Overcoming Challenges in Microalgal Bioprocessing through Data-driven and Computational Approaches. Curr Opin Food Sci., 61:101253. doi:10.1016/j.cofs.2024.101253 

2024

Khanijou JK, Hee YT, Scipion CPM, Chen X, Selvarajoo K (2024). Systems biology approach for enhancing limonene yield by re-engineering Escherichia coli. NPJ Syst Biol Appl., 10(1):109. doi:10.1038/s41540-024-00440-7

Yeo HC, Vijay V, Selvarajoo K (2024). Identifying effective evolutionary strategies-based protocol for uncovering reaction kinetic parameters under the effect of measurement noises. BMC Biology, 22(1):235. doi:10.1186/s12915-024-02019-4

Pabis K, Barardo D, Gruber J, Sirbu O, Malavolta M, Selvarajoo K, Kaeberlein M, Kennedy BK (2004). The impact of short-lived controls on the interpretation of lifespan experiments and progress in geroscience – through the lens of the “900-day rule”, Ageing Research Reviews, 101:102512. doi: 10.1016/j.arr.2024.102512

Rashid MM, Selvarajoo K (2024). Advancing drug-response prediction using multi-modal and -omics machine learning integration (MOMLIN): a case study on breast cancer clinical data. Brief Bioinform., 25(4):bbae300. doi: 10.1093/bib/bbae300

Selvarajoo K, Maurer-Stroh S (2024). Towards multi-omics synthetic data integration. Brief Bioinform., 25(3):bbae213. doi:.10.1093/bib/bbae213

Helmy M, Elhalis H, Rashid MM, Selvarajoo K (2024). Can Digital Twin Efforts Shape Microorganisms-based Alternative Food? Curr Opin Biotechnol., 87:103115. doi:10.1016/j.copbio.2024.103115

Khanijou JK, Hee YT, Selvarajoo K. Identifying Key In Silico Knockout for Enhancement of Limonene Yield Through Dynamic Metabolic Modelling (2024). Methods Mol Biol., 2745:3-19. doi: 10.1007/978-1-0716-3577-3_1

Elhalis H, Helmy M, Ho S, Leow S, Liu Y, Selvarajoo K, Chow Y (2024). Identifying Chlorella vulgaris and Chlorella sorokiniana as sustainable organisms to bioconvert glucosamine into valuable biomass, Biotechnology Notes, 55:13-22. doi.org/10.1016/j.biotno.2024.01.003

Pabis K, Barardo D, Sirbu O,  Selvarajoo K, Gruber J, Kennedy B (2024). A concerted increase in readthrough and intron retention drives transposon expression during aging and senescence. Elife, 12:RP87811, doi: doi.org/10.7554/eLife.87811.2.

2023

Pabis,K., Barardo, D., Gruber, J., Sirbu, O.,  Selvarajoo, K., Kaeberlein, M. & Kennedy, B. K. (2023). The impact of short-lived controls on the interpretation of lifespan experiments and progress in geroscience. bioRxiv 2023.10.08.561459; doi: https://doi.org/10.1101/2023.10.08.561459

Selvarajoo, K. & Giuliani, A. (2023). Systems Biology and Omics Approaches for Complex Human Diseases. Biomolecules, 13(7), 1080, doi: https://doi.org/10.3390/biom13071080.

Sirbu, O., Helmy, M., Giuliani, A., & Selvarajoo, K. (2023). Globally invariant behavior of oncogenes and random genes in cell populations but not at single cell level. npj Systems Biology & Applications, doi: https://doi.org/10.1038/s41540-023-00290-9.

Helmy, M., Elhalis, H., Liu, Y., Chow, Y. & Selvarajoo, K. (2023). Perspective: Multi-omics and Machine Learning Help Unleash the Alternative Food Potential of Microalgae. Advances in Nutrition, doi: https://doi.org/10.1016/j.advnut.2022.11.002.

Helmy, M. & Selvarajoo, K. (2023). Application of GeneCloudOmics: Transcriptomics Data Analytics for Synthetic Biology. In K. Selvarajoo (Ed.), Methods in Molecular Biology (pp. 221-264). New York: Springer, ISBN: 978-1071626160, doi: https://doi.org/10.1007/978-1-0716-2617-7_12. 

2022

Khanijou, J. K., Kulyk, H., Bergès, C. et al. (2022). Metabolomics and modelling approaches for systems metabolic engineering. Metabolic Engineering Communications, 15, e00209, doi: https://doi.org/10.1016/j.mec.2022.e00209.

Selvarajoo, K. (Ed.). (2022). Computational Biology and Machine Learning Approaches for Metabolic Engineering and Synthetic Biology. Methods in Molecular Biology, Springer, New York, ISBN: 978-1071626160.

Yeo, H. C . & Selvarajoo, K. (2022). Machine learning alternative to systems biology should not solely depend on data. Briefings in Bioinformatics, doi: https://doi.org/10.1093/bib/bbac436.

Smith, D. J., Helmy, M., Lindley, N. D. & Selvarajoo, K. (2022). The transformation of our food system using cellular agriculture: What lies ahead and who will lead it? Trends in Food Science & Technology, doi: https://doi.org/10.1016/j.tifs.2022.04.015.

Giuliani, A., Bui, T. T., Helmy, M. & Selvarajoo, K. (2022). Identifying toggle genes from transcriptome-wide scatter: A new perspective for biological regulation. Genomics, 114(1), 215-228, doi: https://doi.org/10.1016/j.ygeno.2021.11.027.

2021

Selvarajoo, K. (2021). The need for integrated systems biology approaches for biotechnological applications. Biotechnology Notes, 2, 39-43, doi: https://doi.org/10.1016/j.biotno.2021.08.002.

Helmy, M. & Selvarajoo, K. (2021). Systems Biology to Understand and Regulate Human Retroviral Proinflammatory Response. Frontiers in Immunology, doi: https://doi.org/10.3389/fimmu.2021.736349.

Helmy, M., Rahul, A., Mohamed, S., Ali Javed, Bui, T. T. & Selvarajoo, K. (2021). GeneCloudOmics: A Data Analytic Cloud Platform for High-Throughput Gene Expression Analysis. Frontiers in Bioinformatics, doi: https://doi.org/10.3389/fbinf.2021.693836.

Selvarajoo, K. (2021). 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, 97-99, doi: https://doi.org/10.1016/j.plrev.2021.04.001.

2020

Helmy, M., Smith, D. & Selvarajoo, K. (2020). Systems biology approaches integrated with artificial intelligence for optimized metabolic engineering. Metabolic Engineering Communications, 11, e00149, doi: https://doi.org/10.1016/j.mec.2020.e00149.

Bui, T. T., Lee, D. & Selvarajoo, K. (2020). ScatLay: utilizing transcriptome-wide noise for identifying and visualizing differentially expressed genes. Scientific Reports, 10, doi: https://doi.org/10.1038/s41598-020-74564-1.

Selvarajoo, K. (2020). Systems Biology Approaches for Understanding Biofilm Response. In S. S. Dhiman (Ed.), Quorum Sensing - Microbial Rules of Life (pp. 9-29). Washington: ACS Publications, doi: https://doi.org/10.1021/bk-2020-1374.ch002.

Bui, T. T. & Selvarajoo, K. (2020). Attractor Concepts to Evaluate the Transcriptome-wide Dynamics Guiding Anaerobic to Aerobic State Transition in Escherichia coli. Scientific Reports, 10, doi: https://doi.org/10.1038/s41598-020-62804-3.