Learned Feature Generation for Molecules

Winter, Patrick; Borgelt, Christian; Berthold, Michael R.

Learned Feature Generation for Molecules

Files

Winter_2-m7ofa8jpw2sa6.pdf(365.15 KB)

Date

2018

Publication type

Contribution to a conference collection

Publication status

Published

Published in

Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings / Duivesteijn, Wouter; Siebes, Arno; Ukkonen, Antti (ed.). - Cham : Springer, 2018. - (Lecture Notes in Computer Science ; 11191). - pp. 380-391. - ISSN 0302-9743. - eISSN 1611-3349. - ISBN 978-3-030-01767-5

Abstract

When classifying molecules for virtual screening, the molecular structure first needs to be converted into meaningful features, before a classifier can be trained. The most common methods use a static algorithm that has been created based on domain knowledge to perform this generation of features. We propose an approach where this conversion is learned by convolutional neural network finding features that are useful for teh task at hand based on the available data. Preliminary results indicate that our current approach can already come up with fetaures that perform similarly well as common methods. Since this approach does not jet use any chemiocal properties, results could be improved in future versions

Subject (DDC)

004 Computer Science

Keywords

Convolutional neural networks; Feature generation; Molecular fetaures; Virtual screening

Conference

17th International Symposium, IDA 2018, Oct 24, 2018 - Oct 26, 2018, ’s-Hertogenbosch, The Netherlands

Cite This

ISO 690

WINTER, Patrick, Christian BORGELT, Michael R. BERTHOLD, 2018. Learned Feature Generation for Molecules. 17th International Symposium, IDA 2018. ’s-Hertogenbosch, The Netherlands, Oct 24, 2018 - Oct 26, 2018. In: DUIVESTEIJN, Wouter, ed., Arno SIEBES, ed., Antti UKKONEN, ed.. Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings. Cham:Springer, pp. 380-391. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-01767-5. Available under: doi: 10.1007/978-3-030-01768-2_31

BibTex

@inproceedings{Winter2018-10-05Learn-44691,
  year={2018},
  doi={10.1007/978-3-030-01768-2_31},
  title={Learned Feature Generation for Molecules},
  number={11191},
  isbn={978-3-030-01767-5},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings},
  pages={380--391},
  editor={Duivesteijn, Wouter and Siebes, Arno and Ukkonen, Antti},
  author={Winter, Patrick and Borgelt, Christian and Berthold, Michael R.}
}

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Bibliography of Konstanz

Yes