bioRxiv (Cold Spring Harbor Laboratory) · 2019 · 211 citations · 7 references
Life SciencesBioinformaticsMolecular BiologyComparative GenomicsComputational BiologyGenomicsGenomic Data IntegrationHomology ModelingPathway ReconstructionProfile Hidden Markov ModelsProtein Sequence AnalysisSequence Similarity SearchAdaptive ThresholdsHidden Markov Model AnnotationHomology DetectionHomology SearchMolecular Function AnnotationOrthologsSequence-based Function AnnotationWeb Server Architecture
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 KofamKOALA, KofamScan, and KOfam are freely available from https://www.genome.jp/tools/kofamkoala/ Contact ogata@kuicr.kyoto-u.ac.jp
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KEGG: Kyoto Encyclopedia of Genes and Genomes
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KEGG: Kyoto Encyclopedia of Genes and Genomes
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Life Sciences, Bioinformatics, High-performance Computing +12
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