SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures.
Tools
Zuo, Zhaorui, Wang, Penglei, Chen, Xiaowei, Tian, Li, Ge, Hui and Qian, Dahong (2021) SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures. BMC bioinformatics, 22 (1). p. 434. ISSN 1471-2105
Official URL: http://www.ncbi.nlm.nih.gov/pubmed/34507532
Abstract
One of the major challenges in precision medicine is accurate prediction of individual patient's response to drugs. A great number of computational methods have been developed to predict compounds activity using genomic profiles or chemical structures, but more exploration is yet to be done to combine genetic mutation, gene expression, and cheminformatics in one machine learning model.
Item Type: | Article |
---|---|
Date Deposited: | 03 Oct 2021 00:45 |
Last Modified: | 03 Oct 2021 00:45 |
URI: | https://oak.novartis.com/id/eprint/45817 |