Gclust: trans-kingdom classification of proteins using automatic individual threshold setting Export

@article{citeulike:4116075, abstract = {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. Availability: Software and data are available at http://gclust.c.u-tokyo.ac.jp/Gclust\_Download.html. Contact: naokisat@bio.c.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btp047}, author = {Sato, Naoki}, citeulike-article-id = {4116075}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btp047}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/25/5/599}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/19158159}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=19158159}, day = {1}, doi = {10.1093/bioinformatics/btp047}, journal = {Bioinformatics}, keywords = {domain\_combination, evolution, phylogeny, protein}, month = {March}, number = {5}, pages = {599--605}, posted-at = {2009-03-01 06:07:40}, priority = {2}, title = {Gclust: trans-kingdom classification of proteins using automatic individual threshold setting}, url = {http://dx.doi.org/10.1093/bioinformatics/btp047}, volume = {25}, year = {2009} }

TY - JOUR ID - citeulike:4116075 L3 - citeulike-article-id:4116075 N2 - 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. Availability: Software and data are available at http://gclust.c.u-tokyo.ac.jp/Gclust_Download.html. Contact: naokisat@bio.c.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btp047 IS - 5 JF - Bioinformatics EP - 605 TI - Gclust: trans-kingdom classification of proteins using automatic individual threshold setting VL - 25 SP - 599 KW - domain_combination KW - evolution KW - phylogeny KW - protein AU - Sato, Naoki PY - 2009/03/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btp047 ER -