Predicting Drug-Disease Associations via Multi-Task Learning Based on Collective Matrix Factorization

Identifying drug-disease associations is integral to drug development. Computationally prioritizing candidate drug-disease associations has attracted growing attention due to its contribution to reducing the cost of laboratory screening. Drug-disease associations involve different association types,...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Feng, Qiu, Yang, Li, Qiaojun, Liu, Shichao, Ni, Fuchuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Bioengineering and Biotechnology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7179666/
https://www.ncbi.nlm.nih.gov/pubmed/32373595
http://dx.doi.org/10.3389/fbioe.2020.00218

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7179666/
https://www.ncbi.nlm.nih.gov/pubmed/32373595
http://dx.doi.org/10.3389/fbioe.2020.00218

Ejemplares similares