title: Gclust: trans-kingdom classification of proteins using automatic individual threshold setting.
abstract: BACKGROUND
  Trans-kingdom protein clustering remained difficult because of large sequence divergence between eukaryotes and prokaryotes and the presence of a transit sequence in organellar proteins. A large-scale protein clustering including such divergent organisms needs a heuristic to efficiently select similar proteins by setting a proper threshold for homologs of each protein. Here a method is described using two similarity measures and organism count.
  
  
  RESULTS
  The Gclust software constructs minimal homolog groups using all-against-all BLASTP results by single-linkage clustering. Major points include (i) estimation of domain structure of proteins; (ii) exclusion of multi-domain proteins; (iii) explicit consideration of transit peptides; and (iv) heuristic estimation of a similarity threshold for homologs of each protein by entropy-optimized organism count method. The resultant clusters were evaluated in the light of power law. The software was used to construct protein clusters for up to 95 organisms.
  
  
  BACKGROUND
  Software and data are available at http://gclust.c.u-tokyo.ac.jp/Gclust_Download.html.
authors.affiliation: Department of Life Sciences, Graduate School of Arts and Sciences, University of Tokyo, Komaba, Meguro-ku, Tokyo, 153-8902, Japan. naokisat@bio.c.u-tokyo.ac.jp
authors.forename: Naoki
authors.initials: N
authors.lastname: Sato
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D011506:Proteins / Q000737:chemistry / Q000145:classification*; D020539:Sequence Analysis, Protein / Q000379:methods; D012984:Software
chemical_list: D011506:Proteins