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dc.contributor.authorRangarajan, Arunen
dc.contributor.authorSchedl, Timen
dc.contributor.authorYook, Karenen
dc.contributor.authorChan, Juancarlosen
dc.contributor.authorHaenel, Stephenen
dc.contributor.authorOtis, Lollyen
dc.contributor.authorFaelten, Sharonen
dc.contributor.authorDePellegrin-Connelly, Traceyen
dc.contributor.authorIsaacson, Ruthen
dc.contributor.authorSkrzypek, Marek Sen
dc.contributor.authorCherry, JMen
dc.contributor.authorSternberg, Paul Wen
dc.contributor.authorMuller, Hans-Michaelen
dc.date.accessioned2011-07-22T20:32:43Z
dc.date.available2011-07-22T20:32:43Z
dc.date.issued2011-05-19en
dc.identifier.issn1471-2105
dc.identifier.urihttp://www.dspace.cam.ac.uk/handle/1810/238517
dc.description.abstractAbstract Background Journal articles and databases are two major modes of communication in the biological sciences, and thus integrating these critical resources is of urgent importance to increase the pace of discovery. Projects focused on bridging the gap between journals and databases have been on the rise over the last five years and have resulted in the development of automated tools that can recognize entities within a document and link those entities to a relevant database. Unfortunately, automated tools cannot resolve ambiguities that arise from one term being used to signify entities that are quite distinct from one another. Instead, resolving these ambiguities requires some manual oversight. Finding the right balance between the speed and portability of automation and the accuracy and flexibility of manual effort is a crucial goal to making text markup a successful venture. Results We have established a journal article mark-up pipeline that links GENETICS journal articles and the model organism database (MOD) WormBase. This pipeline uses a lexicon built with entities from the database as a first step. The entity markup pipeline results in links from over nine classes of objects including genes, proteins, alleles, phenotypes and anatomical terms. New entities and ambiguities are discovered and resolved by a database curator through a manual quality control (QC) step, along with help from authors via a web form that is provided to them by the journal. New entities discovered through this pipeline are immediately sent to an appropriate curator at the database. Ambiguous entities that do not automatically resolve to one link are resolved by hand ensuring an accurate link. This pipeline has been extended to other databases, namely Saccharomyces Genome Database (SGD) and FlyBase, and has been implemented in marking up a paper with links to multiple databases. Conclusions Our semi-automated pipeline hyperlinks articles published in GENETICS to model organism databases such as WormBase. Our pipeline results in interactive articles that are data rich with high accuracy. The use of a manual quality control step sets this pipeline apart from other hyperlinking tools and results in benefits to authors, journals, readers and databases.
dc.languageEnglishen
dc.language.isoen
dc.titleToward an interactive article: integrating journals and biological databasesen
dc.typeArticle
dc.date.updated2011-07-22T20:32:43Z
dc.description.versionRIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.en
dc.rights.holderRangarajan et al.; licensee BioMed Central Ltd.
prism.publicationDate2011en
dcterms.dateAccepted2011-05-19en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2011-05-19en
dc.identifier.eissn1471-2105
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idNational Human Genome Research Institute (NHGRI) (P41HG000739)


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