Combining multiple classifications of chemical structures using consensus clustering
نویسندگان
چکیده
منابع مشابه
Combining multiple classifications of chemical structures using consensus clustering.
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 tha...
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Consensus clustering methods are motivated by the success of combining multiple classifiers in many areas. In this paper, graph-based consensus clustering is used to improve the quality of chemical compound clustering by enhancing the robustness, novelty, consistency and stability of individual clusterings. For this purpose, HyperGraph Partitioning Algorithm (HGPA) [1], was applied. The cluster...
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Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clust...
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ژورنال
عنوان ژورنال: Bioorganic & Medicinal Chemistry
سال: 2012
ISSN: 0968-0896
DOI: 10.1016/j.bmc.2012.03.010