Multilayer network approaches to omics data integration in Digital Twins for cancer research
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916431285714944 |
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| author | Chenel, Hugo Marku, Malvina James, Tim Zinovyev, Andrei Pancaldi, Vera |
| author_facet | Chenel, Hugo Marku, Malvina James, Tim Zinovyev, Andrei Pancaldi, Vera |
| contents | This review examines current and potential applications of DTs in healthcare, focusing on the integration of multi-omics data using multilayer network approaches in cancer research. We discuss methodologies, tools and platforms commonly used for this integration, while highlighting case studies, challenges, and research gaps. Finally, we advocate the need for incorporating diverse data types to produce more effective DTs for personalization of cancer treatments and in silico clinical trials. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_07252 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multilayer network approaches to omics data integration in Digital Twins for cancer research Chenel, Hugo Marku, Malvina James, Tim Zinovyev, Andrei Pancaldi, Vera Molecular Networks Genomics This review examines current and potential applications of DTs in healthcare, focusing on the integration of multi-omics data using multilayer network approaches in cancer research. We discuss methodologies, tools and platforms commonly used for this integration, while highlighting case studies, challenges, and research gaps. Finally, we advocate the need for incorporating diverse data types to produce more effective DTs for personalization of cancer treatments and in silico clinical trials. |
| title | Multilayer network approaches to omics data integration in Digital Twins for cancer research |
| topic | Molecular Networks Genomics |
| url | https://arxiv.org/abs/2410.07252 |