Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response-Reference-Cited by-同舟云学术

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Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response

Published:2019-08 Issue: Volume:166 Page:91-102
ISSN:1046-2023
Container-title:Methods
language:en
Short-container-title:Methods

Author:

Su Ran^ORCID,Liu Xinyi,Wei Leyi^ORCID,Zou Quan^ORCID

Funder

National Key R & D Program of China

National Natural Science Foundation of China

Natural Science Foundation of Tianjin

Publisher

Elsevier BV

Subject

General Biochemistry, Genetics and Molecular Biology,Molecular Biology

Reference60 articles.

1. Tandem: a two-stage approach to maximize interpretability of drug response models based on multiple molecular data types;Aben;Bioinformatics,2016

2. Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data;Aliper;Mol. Pharm.,2016

3. Integrative and personalized QSAR analysis in cancer by kernelized bayesian matrix factorization;Ammad-ud-din;J. Chem. Inf. Model.,2014

4. Extracting drug-drug interactions with attention CNNS;Asada;Proc. BioNLP,2017

5. Drug-target interaction prediction in drug repositioning based on deep semi-supervised learning;Bahi,2018

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