reviewJournal of Chemical Information and ModelingJun 13, 2019Closed access

Deep Learning in Chemistry

Australian National University · ARC Centre of Excellence for Electromaterials Science

PubMed
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Abstract

Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns represented in the data. Over the last eight years, its abilities have increasingly been applied to a wide variety of chemical challenges, from improving computational chemistry to drug and materials design and even synthesis planning. This review aims to explain the concepts of deep learning to chemists from any background and follows this with an overview of the diverse applications demonstrated in the literature. We hope that this will empower the broader chemical community to…

Citation impact

589
total citations
FWCI
27.44
Percentile
100%
References
174
Citations per year

Authors

2

Topics & keywords

Keywords
  • Deep learning
  • Variety (cybernetics)
  • Artificial intelligence
  • Computer science
  • Data science
  • Field (mathematics)
  • Cognitive science
  • Chemistry
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