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Biologically informed NeuralODEs for genome-wide regulatory dynamics
Models that are formulated as ordinary differential equations (ODEs) can accurately explain temporal gene expression patterns and promise to yield new insights into important cellular processes, disease progression, and intervention design. Learning such ODEs is challenging, since we want to predict...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Journal Experts
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055646/ https://www.ncbi.nlm.nih.gov/pubmed/36993392 http://dx.doi.org/10.21203/rs.3.rs-2675584/v1 |