A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations
Abstract Background Understanding the functional effects of non-coding variants is important as they are often associated with gene-expression alteration and disease development. Over the past few years, many computational tools have been developed to predict their functional impact. However, the in...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-06-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-021-03999-8 |