Large-scale evaluation of molecular descriptors by means of clustering

Matthias Dehmer, Frank Emmert-Streib, Shailesh Tripathi

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Molecular descriptors have been explored extensively. From these studies, it is known that a large number of descriptors are strongly correlated and capture similar characteristics of molecules. In this paper, we evaluate 919 Dragon-descriptors of 6 different categories by means of clustering. Also, we analyze these different categories of descriptors also find a subset of descriptors which are least correlated among each other and, hence, characterize molecular graphs distinctively.

Original languageEnglish
Article numbere83956
Pages (from-to)e83956
JournalPLoS ONE
Volume8
Issue number12
DOIs
Publication statusPublished - 31 Dec 2013
Externally publishedYes

Keywords

  • Algorithms
  • Cluster Analysis
  • Humans
  • Models, Molecular
  • Molecular Structure
  • Quantitative Structure-Activity Relationship
  • Software

Fingerprint

Dive into the research topics of 'Large-scale evaluation of molecular descriptors by means of clustering'. Together they form a unique fingerprint.

Cite this