|Title:||KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold|
Endo, Hisashi https://orcid.org/0000-0003-0016-1624 (unconfirmed)
|Author's alias:||遠藤, 寿|
|Publisher:||Oxford University Press (OUP)|
|Abstract:||Summary: KofamKOALA is a web server to assign KEGG Orthologs (KOs) to protein sequences by homology search against a database of profile hidden Markov models (KOfam) with pre-computed adaptive score thresholds. KofamKOALA is faster than existing KO assignment tools with its accuracy being comparable to the best performing tools. Function annotation by KofamKOALA helps linking genes to KEGG resources such as the KEGG pathway maps and facilitates molecular network reconstruction. Availability and implementation: KofamKOALA, KofamScan and KOfam are freely available from GenomeNet (https://www.genome.jp/tools/kofamkoala/). Supplementary information: Supplementary data are available at Bioinformatics online.|
|Rights:||© The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact email@example.com|
|Appears in Collections:||Journal Articles|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.