KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold
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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.
- Type
- preprint
- Published
- 2019-04-08
- Cited by
- 1,844
- References
- 8
- Access
- Open access
- OpenAlex
- https://openalex.org/W2933055545
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:133346763
Keywords
KEGG, Hidden Markov model, Annotation, Computer science, Markov chain
References
- GHOSTX: An Improved Sequence Homology Search Algorithm Using a Query Suffix Array and a Database Suffix Array
- A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation
- MAFFT version 5: improvement in accuracy of multiple sequence alignment
- Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
- KEGG: Kyoto Encyclopedia of Genes and Genomes
- CD-HIT: accelerated for clustering the next-generation sequencing data
- BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences.
- Reconstruction
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