Distance phenomena in high-dimensional chemical descriptor spaces : consequences for similarity-based approaches
2009 Wiley Periodicals, Inc.
| Veröffentlicht in: | Journal of computational chemistry. - 1984. - 30(2009), 14 vom: 15. Nov., Seite 2285-96 |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2009
|
| Zugriff auf das übergeordnete Werk: | Journal of computational chemistry |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't Pharmaceutical Preparations |
| Zusammenfassung: | 2009 Wiley Periodicals, Inc. Measuring the (dis)similarity of molecules is important for many cheminformatics applications like compound ranking, clustering, and property prediction. In this work, we focus on real-valued vector representations of molecules (as opposed to the binary spaces of fingerprints). We demonstrate the influence which the choice of (dis)similarity measure can have on results, and provide recommendations for such choices. We review the mathematical concepts used to measure (dis)similarity in vector spaces, namely norms, metrics, inner products, and, similarity coefficients, as well as the relationships between them, employing (dis)similarity measures commonly used in cheminformatics as examples. We present several phenomena (empty space phenomenon, sphere volume related phenomena, distance concentration) in high-dimensional descriptor spaces which are not encountered in two and three dimensions. These phenomena are theoretically characterized and illustrated on both artificial and real (bioactivity) data |
|---|---|
| Beschreibung: | Date Completed 19.01.2010 Date Revised 31.08.2009 published: Print Citation Status MEDLINE |
| ISSN: | 1096-987X |
| DOI: | 10.1002/jcc.21218 |