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A machine learning approach for genome-wide prediction of morbid and druggable human genes based on systems-level data
BACKGROUND: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-cons...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2010
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045802/ https://www.ncbi.nlm.nih.gov/pubmed/21210975 http://dx.doi.org/10.1186/1471-2164-11-S5-S9 |