Gene

Gene ontology

Biology

Hidden Markov model

Markov chain

Data mining

Computer science

Computational biology

Genetics

Artificial intelligence

KEGG

Gene expression

Machine learning

Annotation

Bioinformatics

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.

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