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dc.contributor.authorKoski, Liisa
dc.contributor.authorGray, Michael
dc.contributor.authorLang, Franz Bernd
dc.contributor.authorBurger, Gertraud
dc.date.accessioned2007-01-05T21:56:47Z
dc.date.available2007-01-05T21:56:47Z
dc.date.issued2005
dc.identifier.urihttp://hdl.handle.net/1866/672
dc.identifier.urihttp://www.biomedcentral.com/1471-2105/6/151
dc.format.extent794086 bytes
dc.format.mimetypeapplication/pdf
dc.rightsCeci est un article en accès libre diffusé sous une licence Creative Commons Paternité laquelle permet une libre utilisation, diffusion et reproduction de l'article sous toutes formes, à la condition de l'attribuer à l'auteur en citant son nom. This is an open access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/2.0
dc.titleAutoFACT: An Automatic Functional Annotation and Classification Tool
dc.typeArticle
dc.contributor.affiliationUniversité de Montréal. Faculté de médecine. Département de biochimie et médecine moléculairefr
dc.identifier.doi10.1186/1471-2105-6-151
dcterms.abstractBACKGROUND:Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets.RESULTS:We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%.CONCLUSION:AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at http://megasun.bch.umontreal.ca/Software/AutoFACT.htm.en
dcterms.descriptionAffiliation: Centre Robert-Cedergren de l'Université de Montréal en bio-informatique et génomique & Département de biochimie, Université de Montréal
dcterms.isPartOfurn:ISSN:1471-2105
UdeM.VersionRioxxVersion acceptée / Accepted Manuscript
oaire.citationTitleBMC bioinformatics
oaire.citationVolume6


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Ceci est un article en accès libre diffusé sous une licence Creative Commons Paternité laquelle permet une libre utilisation, diffusion et reproduction de l'article sous toutes formes, à la condition de l'attribuer à l'auteur en citant son nom. This is an open access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Usage rights : Ceci est un article en accès libre diffusé sous une licence Creative Commons Paternité laquelle permet une libre utilisation, diffusion et reproduction de l'article sous toutes formes, à la condition de l'attribuer à l'auteur en citant son nom. This is an open access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.