Asymmetric Clustering Index in a Case Study of 5-HT1A Receptor Ligands | Zendy

Marek Śmieja | Zendy; Dawid Warszycki | Zendy; Jacek Tabor | Zendy; Andrzej J. Bojarski | Zendy

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Asymmetric Clustering Index in a Case Study of 5-HT1A Receptor Ligands

Author(s) -

Marek Śmieja,

Dawid Warszycki,

Jacek Tabor,

Andrzej J. Bojarski

Publication year - 2014

Publication title -

plos one

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.99

H-Index - 332

ISSN - 1932-6203

DOI - 10.1371/journal.pone.0102069

Subject(s) - cluster analysis , hierarchical clustering , cheminformatics , consensus clustering , single linkage clustering , metric (unit) , similarity (geometry) , computer science , data mining , index (typography) , linkage (software) , partition (number theory) , computational biology , fuzzy clustering , artificial intelligence , mathematics , bioinformatics , chemistry , biology , cure data clustering algorithm , combinatorics , engineering , biochemistry , operations management , world wide web , gene , image (mathematics)

The automatic clustering of chemical compounds is an important branch of chemoinformatics. In this paper the Asymmetric Clustering Index (A ci ) is proposed to assess how well an automatically created partition reflects the reference. The asymmetry allows for a distinction between the fixed reference and the numerically constructed partition. The introduced index is applied to evaluate the quality of hierarchical clustering procedures for 5-HT 1A receptor ligands. We find that the most appropriate combination of parameters for the hierarchical clustering of compounds with a determined activity for this biological target is the Klekota Roth fingerprint combined with the complete linkage function and the Buser similarity metric.

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