KCML: a machine‐learning framework for inference of multi‐scale gene functions from genetic perturbation screens
Abstract Characterising context‐dependent gene functions is crucial for understanding the genetic bases of health and disease. To date, inference of gene functions from large‐scale genetic perturbation screens is based on ad hoc analysis pipelines involving unsupervised clustering and functional enr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-03-01
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| Series: | Molecular Systems Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.15252/msb.20199083 |