Multi-task learning for the simultaneous reconstruction of the human and mouse gene regulatory networks
Abstract The reconstruction of Gene Regulatory Networks (GRNs) from gene expression data, supported by machine learning approaches, has received increasing attention in recent years. The task at hand is to identify regulatory links between genes in a network. However, existing methods often suffer w...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Portfolio
2020-12-01
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| Schriftenreihe: | Scientific Reports |
| Online-Zugang: | https://doi.org/10.1038/s41598-020-78033-7 |
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