KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold
Kyoto University · Instituto de Investigaciones Químicas · +3 more institutions
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.
Citation impact
- FWCI
- 47.25
- Percentile
- 100%
- References
- 9
Authors
7- TATakuya Aramaki
Kyoto University, Instituto de Investigaciones Químicas, Kyoto University Institute for Chemical Research
- RBRomain Blanc‐Mathieu
Kyoto University, Instituto de Investigaciones Químicas, Kyoto University Institute for Chemical Research
- HEHisashi Endo
Kyoto University, Instituto de Investigaciones Químicas, Kyoto University Institute for Chemical Research
- KOKoichi Ohkubo
Kyoto University, Hewlett-Packard (Japan), Instituto de Investigaciones Químicas, Kyoto University Institute for Chemical Research
- MKMinoru Kanehisa
Kyoto University, Instituto de Investigaciones Químicas, Kyoto University Institute for Chemical Research
Topics & keywords
- KEGG
- Annotation
- Computer science
- Hidden Markov model
- Markov chain
- Data mining
- Computational biology
- Artificial intelligence