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Active machine learning-driven experimentation to determine compound effects on protein patterns
High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experiment...
Autores principales: | Naik, Armaghan W, Kangas, Joshua D, Sullivan, Devin P, Murphy, Robert F |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4798950/ https://www.ncbi.nlm.nih.gov/pubmed/26840049 http://dx.doi.org/10.7554/eLife.10047 |
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