title: Development of a spectral clustering method for the analysis of molecular data sets.
abstract: A spectral clustering method is presented and applied to two-dimensional molecular structures, where it has been found particularly useful in the analysis of screening data. The method provides a means to quantify (1) the degree of intermolecular similarity within a cluster and (2) the contribution that the features of a molecule make to a cluster. In an application of the spectral clustering method to an example data set of 125 COX-2 inhibitors, these two criteria were used to place the molecules into clusters of chemically related two-dimensional structures.
authors.affiliation: Computational Chemistry Group, Evotec (UK) Limited, 111 Milton Park, Abingdon, Oxfordshire OX14 4RZ, United Kingdom. mark.brewer@evotec.com
authors.forename: Mark L
authors.initials: ML
authors.lastname: Brewer
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D051546:Cyclooxygenase 2 / Q000737:chemistry; D052246:Cyclooxygenase 2 Inhibitors / Q000737:chemistry*; D016208:Databases, Factual; D004353:Drug Evaluation, Preclinical; D048088:Informatics; D008968:Molecular Conformation; D013329:Structure-Activity Relationship
chemical_list: D052246:Cyclooxygenase 2 Inhibitors; D051546:Cyclooxygenase 2