Publications

Recent publications 

1. Aadhitya, M, Mitra, M & Tyagi, S 2024, Navigating the Multiverse: A Hitchhiker’s Guide to Selecting Harmonisation Methods for Multimodal Biomedical Data, medRxiv.
2. Groenewegen, D., Kalejs, L. & Tyagi, S. 2019, Data Fluency: Building data skills in a sustainable way, Monash University Bridges, viewed 29 May 2024, https://bridges.monash.edu/articles/presentation/Data_Fluency_Building_data_skills_in_a_sustainable_way/9255350.
3. Vahab, N., Bonu, T., Kuhlmann, L., Ramialison, M. & Tyagi, S. 2024, 'Uncovering co-regulatory modules and gene regulatory networks in the heart through machine learning-based analysis of large-scale epigenomic data', ScienceDirect. Available at: https://www.sciencedirect.com/science/article/pii/S0010482524001525?via%3Dihub.
4. Ramakrishnaiah, Y., Macesic, N., Webb, G.I., Peleg, A.Y. & Tyagi, S. 2024, EHR-ML: A generalisable pipeline for reproducible clinical outcomes using electronic health records, medRxiv (Cold Spring Harbor Laboratory). doi: https://doi.org/10.1101/2024.03.02.24302664.
5. Tyagi, S. 2023, Technical Issues in Implementing AI in Healthcare, Chapman and Hall/CRC eBooks, pp. 60–70. doi: https://doi.org/10.1201/9781003262152-4.
6. Chen, T., Abadi, A.J., Cao, K.-A.L. & Tyagi, S. 2023a, multiomics: A user-friendly multi-omics data harmonisation R pipeline. doi: https://doi.org/10.12688/f1000research.53453.2.
7. Chen, T., Tyagi, N., Chauhan, S., Peleg, A.Y. & Tyagi, S. 2023b, genomicBERT and data-free deep-learning model evaluation. doi: https://doi.org/10.1101/2023.05.31.542682.
8. Ramakrishnaiah, Y., Macesic, N., Webb, G.I., Peleg, A.Y. & Tyagi, S. 2023a, 'EHR-QC: A streamlined pipeline for automated electronic health records standardisation and preprocessing to predict clinical outcomes', Journal of Biomedical Informatics, vol. 147, p. 104509. doi: https://doi.org/10.1016/j.jbi.2023.104509.
9. Ramakrishnaiah, Y., Morris, A.P., Dhaliwal, J., Philip, M., Kuhlmann, L. & Tyagi, S. 2023b, 'Linc2function: A Comprehensive Pipeline and Webserver for Long Non-Coding RNA (lncRNA) Identification and Functional Predictions Using Deep Learning Approaches', Epigenomes, vol. 7, no. 3, p. 22. doi: https://doi.org/10.3390/epigenomes7030022.
10. Javier Gómez Ortega, Raubenheimer, D., Tyagi, S., Mirth, C.K. & Piper, M.D. 2023, 'Biosynthetic constraints on amino acid synthesis at the base of the food chain may determine their use in higher-order consumer genomes', PLOS Genetics, vol. 19, no. 2, pp. e1010635–e1010635. doi: https://doi.org/10.1371/journal.pgen.1010635.
11. Mu, A., Klare, W.P., Baines, S.L., Pang, C.N.I., Guérillot, R., Harbison-Price, N., Keller, N., Wilksch, J., Nhu, N.T.K., Phan, M.-D., Keller, B., Nijagal, B., Tull, D., Dayalan, S., Chua, H.H.C., Skoneczny, D., Koval, J., Hachani, A., Shah, A.D. & Neha, N. 2023, 'Integrative omics identifies conserved and pathogen-specific responses of sepsis-causing bacteria', Nature Communications, vol. 14, no. 1. doi: https://doi.org/10.1038/s41467-023-37200-w.
12. Phung, J., Wang, C., Reeders, J., Zakar, T., Paul, J.W., Tyagi, S., Pennell, C.E. & Smith, R. 2023, 'Preterm labor with and without chorioamnionitis is associated with activation of myometrial inflammatory networks: a comprehensive transcriptomic analysis', American Journal of Obstetrics and Gynecology, vol. 228, no. 3, pp. 330.e1–330.e18. doi: https://doi.org/10.1016/j.ajog.2022.08.036.
13. Tyagi, S., Chan, E.-C., Barker, D., McElduff, P., Taylor, K.A., Riveros, C., Singh, E. & Smith, R. 2022, 'Transcriptomic analysis reveals myometrial topologically associated domains linked to the onset of human term labour', Molecular Human Reproduction, vol. 28, no. 3. doi: https://doi.org/10.1093/molehr/gaac003.
14. Chahal, G., Tyagi, S. & Ramialison, M. 2019, 'Navigating the non-coding genome in heart development and Congenital Heart Disease', Differentiation, vol. 107, pp. 11–23. doi: https://doi.org/10.1016/j.diff.2019.05.001.
15. Chen, T., Philip, M., Lê Cao, K.-A. & Tyagi, S. 2021, 'A multi-modal data harmonisation approach for discovery of COVID-19 drug targets', Briefings in Bioinformatics, vol. 22, no. 6, p. bbab185. doi: https://doi.org/10.1093/bib/bbab185.
16. Javier Gómez Ortega, Tyagi, S., Mirth, C.K. & Piper, M.D.W. 2021, 'The Biosynthetic Costs of Amino Acids at the Base of the Food Chain Determine Their Use in Higher-order Consumer Genomes', doi: https://doi.org/10.1101/2021.11.03.467059.
17. Philip, M., Chen, T. & Tyagi, S. 2021, 'A Survey of Current Resources to Study lncRNA-Protein Interactions', Non-Coding RNA, vol. 7, no. 2, p. 33. doi: https://doi.org/10.3390/ncrna70200.
18. Philip, M., Chen, T. & Tyagi, S. 2021, 'A Survey of Current Resources to Study lncRNA-Protein Interactions', Non-Coding RNA, vol. 7, no. 2, p. 33. doi: https://doi.org/10.3390/ncrna7020033.
19. Saaristo, M., Craft, J.A., Tyagi, S., Johnstone, C.J., Allinson, M., Ibrahim, K.E. & Bob 2021, 'Transcriptome-wide changes associated with the reproductive behaviour of male guppies exposed to 17α-ethinyl estradiol', Environmental Pollution, vol. 270, pp. 116286–116286. doi: https://doi.org/10.1016/j.envpol.2020.116286.
20. Chen, T. & Tyagi, S. 2020, 'Integrative computational epigenomics to build data-driven gene regulation hypotheses', GigaScience, vol. 9, no. 6. doi: https://doi.org/10.1093/gigascience/giaa064.
21. Ramakrishnaiah, Y., Kuhlmann, L. & Tyagi, S. 2020, 'Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA)', Computers in Biology and Medicine, vol. 127, p. 104028. doi: https://doi.org/10.1016/j.compbiomed.2020.104028.
22. Chen, T., Cao, K.-A.L. & Tyagi, S. 2020, 'Multi-omics data integration for the discovery of COVID-19 drug targets', F1000Research, vol. 9. doi: https://doi.org/10.7490/f1000research.1118023.1.
23. John Van Horn, Abe, S., Ambite, J.L., Attwood, T.K., Beard, N., Bellis, L.J., Bhattrai, A., Bull, A., Burns, G., Fierro, L., Gordon, J., Grethe, J.S., Kamdar, J., Lei, X., Lerman, K., McGrath, A., Mulder, N., O’Driscoll, C., Stewart, C. & Tyagi, S. 2019, 'Advancing the international data science workforce through shared training and education', F1000Research, vol. 8, p. 251. doi: https://doi.org/10.12688/f1000research.18357.1.
24. Ngoc, T., Tyagi, S., D’Cunha, G., Bhave, M., Crawford, R.J. & Ivanova, E.P. 2019a, 'Computational prediction of microRNAs in marine bacteria of the genus Thalassospira', PLOS ONE, vol. 14, no. 3, pp. e0212996–e0212996. doi: https://doi.org/10.1371/journal.pone.0212996.
25. Delay, C., Chapman, K., Taleski, M., Wang, Y., Tyagi, S., Xiong, Y., Imin, N. & Djordjevic, M.A. 2019, 'CEP3 levels affect starvation-related growth responses of the primary root', Journal of Experimental Botany, vol. 70, no. 18, pp. 4763–4774. doi: https://doi.org/10.1093/jxb/erz270.
26. Fahey, J.K., Williams, S.M., Tyagi, S., Powell, D.R., Hallab, J.C., Chahal, G., Ramialison, M.S.M. & White, A.J. 2018, 'The Intercellular Tight Junction and Spontaneous Coronary Artery Dissection', Journal of the American College of Cardiology, vol. 72, no. 14, pp. 1752–1753. doi: https://doi.org/10.1016/j.jacc.2018.07.040.
27. Stefanidis, A., Wiedmann, N.M., Tyagi, S., Allen, A.M., Watt, M.J. & Oldfield, B.J. 2018, 'Insights into the neurochemical signature of the innervation of beige fat', Molecular Metabolism, vol. 11, pp. 47–58. doi: https://doi.org/10.1016/j.molmet.2018.01.024.
28. Tsai, T.-S., Tyagi, S. & St John, J.C. 2018, 'The molecular characterisation of mitochondrial DNA deficient oocytes using a pig model', Human Reproduction (Oxford, England), vol. 33, no. 5, pp. 942–953. doi: https://doi.org/10.1093/humrep/dey052.
29. Schneider, M.V., Griffin, P.C., Tyagi, S., Flannery, M., Dayalan, S., Gladman, S., Watson-Haigh, N., Bayer, P.E., Charleston, M., Cooke, I., Cook, R., Edwards, R.J., Edwards, D., Gorse, D., McConville, M., Powell, D., Wilkins, M.R. & Lonie, A. 2017, 'Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia', Briefings in Bioinformatics, vol. 20, no. 2, pp. 384–389. doi: https://doi.org/10.1093/bib/bbx071.