Combining multiple classifications of chemical structures using consensus clustering
| Autor: | John D. Holliday, Peter Willett, Chia-Wei Chu |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Fuzzy clustering
Molecular Structure Databases Pharmaceutical Chemistry Organic Chemistry Clinical Biochemistry Single-linkage clustering Correlation clustering Pharmaceutical Science computer.software_genre Biochemistry Hierarchical clustering Pharmaceutical Preparations CURE data clustering algorithm Drug Discovery Consensus clustering Cluster Analysis Molecular Medicine FLAME clustering Data mining Cluster analysis Molecular Biology computer |
| Zdroj: | Bioorganic & Medicinal Chemistry. 20:5366-5371 |
| ISSN: | 0968-0896 |
| Popis: | Consensus clustering involves combining multiple clusterings of the same set of objects to achieve a single clustering that will, hopefully, provide a better picture of the groupings that are present in a dataset. This Letter reports the use of consensus clustering methods on sets of chemical compounds represented by 2D fingerprints. Experiments with DUD, IDAlert, MDDR and MUV data suggests that consensus methods are unlikely to result in significant improvements in clustering effectiveness as compared to the use of a single clustering method. |
| Databáze: | OpenAIRE |
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