Is Machine Learning the Future of Theoretical Chemistry?

Authors

  • K. Berka Department of Physical Chemistry, RCPTM, Faculty of Science, Palacký University Olomouc, Olomouc
  • Š. Sršeň Department of Physical Chemistry, University of Chemistry and Technology, Prague
  • P. Slavíček Department of Physical Chemistry, University of Chemistry and Technology, Prague | J. Heyrovský Institute of Physical Chemistry of the CAS, Prague

Keywords:

machine learning, artificial intelligence, QSAR, quantum chemistry, theoretical chemistry, neural networks

Abstract

The application of the methods of machine learning in chemistry is briefly summarized in the present work. We first explain the basic concepts of artificial intelligence and machine learning. Next, the applications in two particular areas are discussed: searching relations between the structure and biological activity of molecules and using the techniques of machine learning in quantum chemistry as well as in other fields of theoretical chemistry.  The evolutionary character of the machine learning approaches is emphasized. A fast development is witnessed in the field which, however, gradually follows the previous development in using statistical techniques in chemistry.

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Published

2018-10-15

How to Cite

Berka, K., Sršeň, Š., & Slavíček, P. (2018). Is Machine Learning the Future of Theoretical Chemistry?. Chemické Listy, 112(10), 640–647. Retrieved from http://blog.chemicke-listy.cz/ojs3/index.php/chemicke-listy/article/view/3187

Issue

Vol. 112 No. 10 (2018)

Section

Articles