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...

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Hlavní autoři: Costa, Pedro R, Acencio, Marcio L, Lemke, Ney
Médium: Artigo
Jazyk:Inglês
Vydáno: BioMed Central 2010
Témata:
Proceedings
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC3045802/
https://ncbi.nlm.nih.gov/pubmed/21210975
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2164-11-S5-S9
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