An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data
Abstract Background The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed to predict human essential genes from popul...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-09-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-023-05481-z |