Communication

You have free access to this content

Chemical Descriptors Are More Important Than Learning Algorithms for Modelling

  1. S. Stanley Young1,*,
  2. Fei Yuan2,
  3. Mu Zhu3

Article first published online: 11 SEP 2012

DOI: 10.1002/minf.201200031

Issue

Molecular Informatics

Molecular Informatics

Volume 31, Issue 10, pages 707–710, October 2012

Additional Information

How to Cite

Young, S. S., Yuan, F. and Zhu, M. (2012), Chemical Descriptors Are More Important Than Learning Algorithms for Modelling. Mol. Inf., 31: 707–710. doi: 10.1002/minf.201200031

Author Information

  1. 1

    National Institute of Statistical Sciences, 19 T. W. Alexander Drive, P. O. Box 14006, Research Triangle Park, NC 27709-4006, USA

  2. 2

    Population Health Research Institute, McMaster Clinic, Hamilton General Hospital, 237 Barton Street East, Hamilton, Ontario, Canada L8L 2X2

  3. 3

    Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada N2L 3G1

*National Institute of Statistical Sciences, 19 T. W. Alexander Drive, P. O. Box 14006, Research Triangle Park, NC 27709-4006, USA

Publication History

  1. Issue published online: 12 OCT 2012
  2. Article first published online: 11 SEP 2012
  3. Manuscript Accepted: 23 JUL 2012
  4. Manuscript Received: 3 APR 2012

Funded by

  • Natural Sciences and Engineering Research Council (NSERC) of Canada
  • Mathematics of Information Technology and Complex Systems (MITACS) Network
  • University of Waterloo

SEARCH

SEARCH BY CITATION

ARTICLE TOOLS

View Full Article (HTML) Get PDF (128K)

Keywords:

  • Average precision;
  • Boosting;
  • Ensemble algorithms;
  • Kernel algorithms;
  • Random forest;
  • Support vector machine;
  • Virtual screening
Thumbnail image of graphical abstract
View Full Article (HTML) Get PDF (128K)