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| Pàgina inicial > Articles > Articles publicats > Text mining and expert curation to develop a database on psychiatric diseases and their genes |
(Institut Hospital del Mar d'Investigacions Mèdiques) (Institut Hospital del Mar d'Investigacions Mèdiques) (Universitat Autònoma de Barcelona. Institut de Neurociències) (Institut Hospital del Mar d'Investigacions Mèdiques) (Institut Hospital del Mar d'Investigacions Mèdiques) (Universitat Autònoma de Barcelona. Institut de Neurociències) (Institut Hospital del Mar d'Investigacions Mèdiques) (Universitat Autònoma de Barcelona. Institut de Neurociències) (Institut Hospital del Mar d'Investigacions Mèdiques) (Institut Hospital del Mar d'Investigacions Mèdiques)| Data: | 2017 |
| Resum: | 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 () 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 associations (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 : PsyGeNET corpus:. |
| Ajuts: | Instituto de Salud Carlos III PI13-00082 Instituto de Salud Carlos III CP10-00524 Instituto de Salud Carlos III CPII16-00026 Instituto de Salud Carlos III PT13-0001-0023 Instituto de Salud Carlos III RD16-0017-0007 Instituto de Salud Carlos III RD16-0017-0010 Instituto de Salud Carlos III RD16-0017-0001 Ministerio de Economía y Competitividad MDM-2014-0370 |
| Nota: | Altres ajuts: We received support from 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). , of the PE I þ Dþi 2013- 2016, funded by ISCIII and FEDER. Funding for open access: EU H2020 Programme 2014-2020 under grant agreements no. 634143 (MedBioinformatics). |
| Drets: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.  |
| Llengua: | Anglès |
| Document: | Article ; recerca ; Versió publicada |
| Publicat a: | Database, Vol. 2017 (june 2017) , ISSN 1758-0463 |
