Predicting drug-target interactions by dual-network integrated logistic matrix factorization

In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug...

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Detalles Bibliográficos
Autores principales: Hao, Ming, Bryant, Stephen H., Wang, Yanli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5227688/
https://www.ncbi.nlm.nih.gov/pubmed/28079135
http://dx.doi.org/10.1038/srep40376

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5227688/
https://www.ncbi.nlm.nih.gov/pubmed/28079135
http://dx.doi.org/10.1038/srep40376

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