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A Novel Framework for Predicting In Vivo Toxicities from In Vitro Data Using Optimal Methods for Dense and Sparse Matrix Reordering and Logistic Regression
In this work, we combine the strengths of mixed-integer linear optimization (MILP) and logistic regression for predicting the in vivo toxicity of chemicals using only their measured in vitro assay data. The proposed approach utilizes a biclustering method based on iterative optimal reordering (DiMag...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2010
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2955210/ https://ncbi.nlm.nih.gov/pubmed/20702588 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/toxsci/kfq233 |
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