Deep learning-based transcriptome data classification for drug-target interaction prediction.

Journal: BMC genomics

Published Date: Sep 24, 2018

Abstract

BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded by the wide range of data platforms and data scarcity.

Authors

Lingwei Xie

Xiamen University, Xiamen, 361005, China.
Song He

Department of Biotechnology, Beijing Institute of Radiation Medicine, 27 Taiping Street, Haidian District, Beijing, 100850, China.
Xinyu Song

Beijing Institute of Radiation Medicine, Beijing, 100850, China.
Xiaochen Bo

Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, China.
Zhongnan Zhang

Keywords

Algorithms Computer Simulation Databases, Factual Drug Discovery Drug Interactions Gene Expression Profiling Humans Machine Learning Models, Theoretical Molecular Targeted Therapy Proteins Transcriptome

External Resources

View on PubMed Access via DOI PubMed (30255785)

Deep learning-based transcriptome data classification for drug-target interaction prediction.

Abstract

Authors

Keywords

External Resources

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