Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology
Link
http://link.springer.com/content/pdf/10.1186/s12859-019-2910-6.pdf
Reference51 articles.
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3. Ammad-Ud-Din M, Georgii E, Gonen M, Laitinen T, Kallioniemi O, Wennerberg K, Poso A, Kaski S. Integrative and personalized qsar analysis in cancer by kernelized bayesian matrix factorization. J Chem Inf Model. 2014; 54(8):2347–59.
4. Haider S, Rahman R, Ghosh S, Pal R. A copula based approach for design of multivariate random forests for drug sensitivity prediction. PLoS ONE. 2015; 10(12):0144490.
5. Mitchell JB. Machine learning methods in chemoinformatics. Wiley Interdiscip Rev Comput Mol Sci. 2014; 4(5):468–81.
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