Text mining and expert curation to develop a database on psychiatric diseases and their genes

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  • dc.contributor.author Gutiérrez Sacristán, Albaca
  • dc.contributor.author Bravo Serrano, Àlex, 1984-ca
  • dc.contributor.author Portero Tresserra, Martaca
  • dc.contributor.author Valverde Granados, Olgaca
  • dc.contributor.author Leis Machín, Angela 1974-ca
  • dc.contributor.author Mayer, Miguel Ángel, 1960-ca
  • dc.contributor.author Warnault, Vincentca
  • dc.contributor.author Sanz, Ferranca
  • dc.contributor.author Furlong, Laura I., 1971-ca
  • dc.date.accessioned 2018-03-15T09:18:37Z
  • dc.date.available 2018-03-15T09:18:37Z
  • dc.date.issued 2017
  • dc.description.abstract Psychiatric disorders constitute one of the main causes of disability worldwide. During the past years, considerable research has been conducted on the genetic architecture of such diseases, although little understanding of their etiology has been achieved. The difficulty to access up-to-date, relevant genotype-phenotype information has hampered the application of this wealth of knowledge to translational research and clinical practice in order to improve diagnosis and treatment of psychiatric patients. PsyGeNET (http://www.psygenet.org/) has been developed with the aim of supporting research on the genetic architecture of psychiatric diseases, by providing integrated and structured accessibility to their genotype-phenotype association data, together with analysis and visualization tools. In this article, we describe the protocol developed for the sustainable update of this knowledge resource. It includes the recruitment of a team of domain experts in order to perform the curation of the data extracted by text mining. Annotation guidelines and a web-based annotation tool were developed to support the curators' tasks. A curation workflow was designed including a pilot phase and two rounds of curation and analysis phases. Negative evidence from the literature on gene-disease associ- ations (GDAs) was taken into account in the curation process. We report the results of the application of this workflow to the curation of GDAs for PsyGeNET, including the analysis of the inter-annotator agreement and suggest this model as a suitable approach for the sustainable development and update of knowledge resources. Database URL: http://www.psygenet.org. PsyGeNET corpus: http://www.psygenet.org/ds/PsyGeNET/results/psygenetCorpus.tar
  • dc.description.sponsorship We received support from ISCIII-FEDER (PI13/00082, CP10/00524, CPII16/00026), IMI-JU under grants agreements no. 115191 (Open PHACTS)] and no. 115372 (EMIF), resources of which are composed of financial contribution from the EU-FP7 (FP7/2007-2013) and EFPIA companies in kind contribution, and the EU H2020 Programme 2014-2020 under grant agreements no. 634143 (MedBioinformatics) and no. 676559 (Elixir-Excelerate). The Research Programme on Biomedical Informatics (GRIB) is a member of the Spanish National Bioinformatics Institute (INB), PRB2-ISCIII and is supported by grant PT13/0001/0023, of the PE I + D+i 2013-2016, funded by ISCIII and FEDER. MRA, SMR and MCBG are supported RD16/0017/0007; OV, FF and MT are supported by RD16/0017/0010; and AS and FJP are supported by RD16/0017/0001, by Instituto de Salud Carlos III, Red de Trastornos Adictivos (RTA-Retics-ISCIII). AGS acknowledges financial support from the Spanish Ministry of Economy and Competitiveness, through the 'María de Maeztu' Programme for Units of Excellence in R&D (MDM-2014-0370). Funding for open access: EU H2020 Programme 2014-2020 under grant agreements no. 634143 (MedBioinformatics).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Gutierrez-Sacristan A, Bravo A, Portero-Tresserra M, Valverde O, Armario A, Blanco-Gandia MC et al. Text mining and expert curation to develop a database on psychiatric diseases and their genes. Database (Oxford). 2017 Jan 1;2017:bax043. DOI: 10.1093/database/bax043
  • dc.identifier.doi http://dx.doi.org/10.1093/database/bax043
  • dc.identifier.issn 1758-0463
  • dc.identifier.uri http://hdl.handle.net/10230/34136
  • dc.language.iso eng
  • dc.publisher Oxford University Pressca
  • dc.relation.ispartof Database (Oxford). 2017 Jan 1;2017:bax043
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/115372
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/634143
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/676559
  • dc.rights © The Author(s) 2017. Published by Oxford University Press. This is an Open Access article distributed under the terms of a Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Mental disorders
  • dc.subject.keyword Data curation
  • dc.subject.keyword Data mining
  • dc.title Text mining and expert curation to develop a database on psychiatric diseases and their genesca
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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