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GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs
SUMMARY: Support Vector Machines with gapped k-mer kernels (gkm-SVMs) have been used to learn predictive models of regulatory DNA sequence. However, interpreting predictive sequence patterns learned by gkm-SVMs can be challenging. Existing interpretation methods such as deltaSVM, in-silico mutagenes...
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| Udgivet i: | Bioinformatics |
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| Main Authors: | , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Oxford University Press
2019
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6612808/ https://ncbi.nlm.nih.gov/pubmed/31510661 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btz322 |
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