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https://hdl.handle.net/10356/180054| Title: | Towards multi-omics synthetic data integration | Authors: | Selvarajoo, Kumar Maurer-Stroh, Sebastian |
Keywords: | Medicine, Health and Life Sciences | Issue Date: | 2024 | Source: | Selvarajoo, K. & Maurer-Stroh, S. (2024). Towards multi-omics synthetic data integration. Briefings in Bioinformatics, 25(3). https://dx.doi.org/10.1093/bib/bbae213 | Journal: | Briefings in Bioinformatics | Abstract: | Across many scientific disciplines, the development of computational models and algorithms for generating artificial or synthetic data is gaining momentum. In biology, there is a great opportunity to explore this further as more and more big data at multi-omics level are generated recently. In this opinion, we discuss the latest trends in biological applications based on process-driven and data-driven aspects. Moving ahead, we believe these methodologies can help shape novel multi-omics-scale cellular inferences. | URI: | https://hdl.handle.net/10356/180054 | ISSN: | 1467-5463 | DOI: | 10.1093/bib/bbae213 | Schools: | School of Biological Sciences | Organisations: | Bioinformatics Institute, A*STAR Yong Loo Lin School of Medicine, NUS Synthetic Biology for Clinical and Technological Innovation, NUS |
Rights: | © The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
| Appears in Collections: | SBS Journal Articles |
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| bbae213.pdf | 615.89 kB | Adobe PDF |  View/Open |
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