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. 2020 Apr 1;36(7):2251-2252.
doi: 10.1093/bioinformatics/btz859.

KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold

Takuya Aramaki  1 , Romain Blanc-Mathieu  1 , Hisashi Endo  1 , Koichi Ohkubo  1   2 , Minoru Kanehisa  1 , Susumu Goto  3 , Hiroyuki Ogata  1
Affiliations

KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold

Takuya Aramaki et al. Bioinformatics. .

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.

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