title: A geometric clustering algorithm with applications to structural data.
abstract: An important feature of structural data, especially those from structural determination and protein-ligand docking programs, is that their distribution could be mostly uniform. Traditional clustering algorithms developed specifically for nonuniformly distributed data may not be adequate for their classification. Here we present a geometric partitional algorithm that could be applied to both uniformly and nonuniformly distributed data. The algorithm is a top-down approach that recursively selects the outliers as the seeds to form new clusters until all the structures within a cluster satisfy a classification criterion. The algorithm has been evaluated on a diverse set of real structural data and six sets of test data. The results show that it is superior to the previous algorithms for the clustering of structural data and is similar to or better than them for the classification of the test data. The algorithm should be especially useful for the identification of the best but minor clusters and for speeding up an iterative process widely used in NMR structure determination.
authors.affiliation: College of Computer Science and Technology, Jilin University , Changchun, P.R. China .
authors.forename: Shutan
authors.initials: S
authors.lastname: Xu
authors.forename: Shuxue
authors.initials: S
authors.lastname: Zou
authors.forename: Lincong
authors.initials: L
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D066264:Datasets as Topic; D015195:Drug Design; D006801:Humans; D062105:Molecular Docking Simulation; D019906:Nuclear Magnetic Resonance, Biomolecular; D051738:Origin Recognition Complex / Q000037:antagonists & inhibitors / Q000737:chemistry*; D011487:Protein Conformation; D018168:Receptors, Retinoic Acid / Q000037:antagonists & inhibitors / Q000737:chemistry*; D055755:SOXD Transcription Factors / Q000037:antagonists & inhibitors / Q000737:chemistry*; D012441:Saccharomyces cerevisiae / Q000737:chemistry / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000037:antagonists & inhibitors / Q000737:chemistry*
chemical_list: C497215:ORC2 protein, S cerevisiae; D051738:Origin Recognition Complex; D018168:Receptors, Retinoic Acid; D055755:SOXD Transcription Factors; D029701:Saccharomyces cerevisiae Proteins; C082928:retinoic acid binding protein II, cellular
keywords: algorithms; distance geometry; drug design; protein structure