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

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          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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          GHOSTX: An Improved Sequence Homology Search Algorithm Using a Query Suffix Array and a Database Suffix Array

          Shuji Suzuki, Masanori Kakuta, Takashi Ishida … (2014)
          DNA sequences are translated into protein coding sequences and then further assigned to protein families in metagenomic analyses, because of the need for sensitivity. However, huge amounts of sequence data create the problem that even general homology search analyses using BLASTX become difficult in terms of computational cost. We designed a new homology search algorithm that finds seed sequences based on the suffix arrays of a query and a database, and have implemented it as GHOSTX. GHOSTX achieved approximately 131–165 times acceleration over a BLASTX search at similar levels of sensitivity. GHOSTX is distributed under the BSD 2-clause license and is available for download at http://www.bi.cs.titech.ac.jp/ghostx/. Currently, sequencing technology continues to improve, and sequencers are increasingly producing larger and larger quantities of data. This explosion of sequence data makes computational analysis with contemporary tools more difficult. We offer this tool as a potential solution to this problem.
          Article 0 comments Cited 40 times – based on 0 reviews     Review now
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            Author and article information

            Contributors
            Alfonso Valencia: Role: Associate Editor
            Journal
            Journal ID (nlm-ta): Bioinformatics
            Journal ID (iso-abbrev): Bioinformatics
            Journal ID (publisher-id): bioinformatics
            Title: Bioinformatics
            Publisher: Oxford University Press
            ISSN (Print): 1367-4803
            ISSN (Electronic): 1367-4811
            Publication date (Print): 01 April 2020
            Publication date (Electronic): 19 November 2019
            Publication date PMC-release: 19 November 2019
            Volume: 36
            Issue: 7
            Pages: 2251-2252
            Affiliations
            [1 ] Bioinformatics Center, Institute for Chemical Research, Kyoto University , Gokasho, Uji, Kyoto 611-0011
            [2 ] Hewlett-Packard Japan Ltd. , Koto-ku, Tokyo 136-8711
            [3 ] Database Center for Life Science, Research Organization of Information and Systems , Kashiwa, Chiba 277-0871, Japan
            Author notes
            To whom correspondence should be addressed. E-mail: ogata@ 123456kuicr.kyoto-u.ac.jp
            Article
            Publisher ID: btz859
            DOI: 10.1093/bioinformatics/btz859
            PMC ID: 7141845
            PubMed ID: 31742321
            SO-VID: 3d59346b-b262-4f5b-9466-e747d7edfbfe
            Copyright © © The Author(s) 2019. Published by Oxford University Press.
            License:

            This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

            History
            Date received : 09 April 2019
            Date revision received : 02 October 2019
            Date accepted : 16 November 2019
            Page count
            Pages: 2
            Funding
            Funded by: JSPS/MEXT/KAKENHI;
            Award ID: 26430184
            Award ID: 18H02279
            Award ID: 16H06429
            Award ID: 16K21723
            Award ID: 16H06437
            Funded by: Collaborative Research Program of the Institute for Chemical Research, Kyoto University ;
            Award ID: 2018-30
            Categories
            Subject: Applications Notes
            Subject: Genome Analysis

            ScienceOpen disciplines: Bioinformatics & Computational biology
            Data availability:
            ScienceOpen disciplines: Bioinformatics & Computational biology

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