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Prediction of driver variants in the cancer genome via machine learning methodologies
Sequencing technologies have led to the identification of many variants in the human genome which could act as disease-drivers. As a consequence, a variety of bioinformatics tools have been proposed for predicting which variants may drive disease, and which may be causatively neutral. After briefly...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Oxford University Press
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293831/ https://www.ncbi.nlm.nih.gov/pubmed/33094325 http://dx.doi.org/10.1093/bib/bbaa250 |