| Literature DB >> 29366762 |
Hongming Chen1, Ola Engkvist2, Yinhai Wang3, Marcus Olivecrona2, Thomas Blaschke2.
Abstract
Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other machine learning algorithms in areas such as image and voice recognition, natural language processing, among others. The first wave of applications of deep learning in pharmaceutical research has emerged in recent years, and its utility has gone beyond bioactivity predictions and has shown promise in addressing diverse problems in drug discovery. Examples will be discussed covering bioactivity prediction, de novo molecular design, synthesis prediction and biological image analysis.Entities:
Mesh:
Year: 2018 PMID: 29366762 DOI: 10.1016/j.drudis.2018.01.039
Source DB: PubMed Journal: Drug Discov Today ISSN: 1359-6446 Impact factor: 7.851