Gclust: trans-kingdom classification of proteins using automatic individual threshold setting
Gclust: trans-kingdom classification of proteins using automatic individual threshold setting
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DOI：
10.1093/bioinformatics/btp047
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发表时间：
2009-03-01
期刊：
影响因子：
5.8
通讯作者：
Sato, Naoki
中科院分区：
文献类型：
--
作者：
Sato, Naoki
Motivation: 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.
