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A systematic approach to identify novel cancer drug targets using machine learning, inhibitor design and high-throughput screening
We present an integrated approach that predicts and validates novel anti-cancer drug targets. We first built a classifier that integrates a variety of genomic and systematic datasets to prioritize drug targets specific for breast, pancreatic and ovarian cancer. We then devised strategies to inhibit...
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| Autors principals: | , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2014
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4143549/ https://ncbi.nlm.nih.gov/pubmed/25165489 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13073-014-0057-7 |
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