Towards multi-omics synthetic data integration
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...
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| Format: | Journal Article |
| Language: | English |
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2024
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| Online Access: | https://hdl.handle.net/10356/180054 |
| _version_ | 1826115665149296640 |
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| author | Selvarajoo, Kumar Maurer-Stroh, Sebastian |
| author2 | School of Biological Sciences |
| author_facet | School of Biological Sciences Selvarajoo, Kumar Maurer-Stroh, Sebastian |
| author_sort | Selvarajoo, Kumar |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:58:51Z |
| format | Journal Article |
| id | ntu-10356/180054 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:58:51Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1800542024-09-16T15:32:06Z Towards multi-omics synthetic data integration Selvarajoo, Kumar Maurer-Stroh, Sebastian School of Biological Sciences Bioinformatics Institute, A*STAR Yong Loo Lin School of Medicine, NUS Synthetic Biology for Clinical and Technological Innovation, NUS Medicine, Health and Life Sciences Synthetic data Multi-omics 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. Agency for Science, Technology and Research (A*STAR) Published version The authors thank the Bioinformatics Institute, A∗STAR, for funding and support. 2024-09-11T04:46:16Z 2024-09-11T04:46:16Z 2024 Journal Article 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 1467-5463 https://hdl.handle.net/10356/180054 10.1093/bib/bbae213 38711370 2-s2.0-85192586359 3 25 en Briefings in Bioinformatics © 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. application/pdf |
| spellingShingle | Medicine, Health and Life Sciences Synthetic data Multi-omics Selvarajoo, Kumar Maurer-Stroh, Sebastian Towards multi-omics synthetic data integration |
| title | Towards multi-omics synthetic data integration |
| title_full | Towards multi-omics synthetic data integration |
| title_fullStr | Towards multi-omics synthetic data integration |
| title_full_unstemmed | Towards multi-omics synthetic data integration |
| title_short | Towards multi-omics synthetic data integration |
| title_sort | towards multi omics synthetic data integration |
| topic | Medicine, Health and Life Sciences Synthetic data Multi-omics |
| url | https://hdl.handle.net/10356/180054 |
| work_keys_str_mv | AT selvarajookumar towardsmultiomicssyntheticdataintegration AT maurerstrohsebastian towardsmultiomicssyntheticdataintegration |