NrGe-DTL: a computational framework for cancer drug response prediction based on deep transfer learning from combined denoised genomic profiles and chemical structure embedding of drugs-Reference-Cited by-同舟云学术

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NrGe-DTL: a computational framework for cancer drug response prediction based on deep transfer learning from combined denoised genomic profiles and chemical structure embedding of drugs

Published:2023-12-05 Issue: Volume:28 Page:440-445
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
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Author:

Zhang Yuchen¹,Lian Linghang¹,Yang Xuhua¹

Affiliation:

1. Zhejiang University of Technology,Coll. of Computer Science and Technology,Hangzhou,China

Funder

Department of Education of Zhejiang Province

Health

Natural Science Foundation of Zhejiang Province

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385310.pdf?arnumber=10385310

Reference34 articles.

1. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity

2. The Cancer Genome Atlas Pan-Cancer analysis project

3. COSMIC: the Catalogue Of Somatic Mutations In Cancer

4. Next-generation sequencing to guide cancer therapy

5. Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells

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