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LAS: A Lipid Annotation Service Capable of Explaining the Annotations It Generates.
Fernández-López, Mariano; Gil-de-la-Fuente, Alberto; Godzien, Joanna; Rupérez, Francisco J; Barbas, Coral; Otero, Abraham.
Afiliação
  • Fernández-López M; Department of Information Technology, Escuela Politécnica Superior, Universidad CEU-San Pablo, Campus Montepríncipe, Boadilla del Monte, Madrid 28668, Spain.
  • Gil-de-la-Fuente A; Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia, Universidad CEU-San Pablo, Campus Montepríncipe, Boadilla del Monte, Madrid, 28668, Spain.
  • Godzien J; Department of Information Technology, Escuela Politécnica Superior, Universidad CEU-San Pablo, Campus Montepríncipe, Boadilla del Monte, Madrid 28668, Spain.
  • Rupérez FJ; Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia, Universidad CEU-San Pablo, Campus Montepríncipe, Boadilla del Monte, Madrid, 28668, Spain.
  • Barbas C; Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia, Universidad CEU-San Pablo, Campus Montepríncipe, Boadilla del Monte, Madrid, 28668, Spain.
  • Otero A; Clinical Research Centre, Medical University of Bialystok, Poland.
Comput Struct Biotechnol J ; 17: 1113-1122, 2019.
Article em En | MEDLINE | ID: mdl-31462967
The Lipid Annotation Service (LAS) is a representational state transfer (REST) application programming interface (API) service designed to aid researchers performing lipid annotation. It assigns certainty levels (very unlikely, unlikely, likely, and very likely) to the putative annotations received as input and explains the rationale of such assignments. Its rules, obtained from the Centre for Metabolomics and Bioanalysis (CEMBIO) and from a literature review, enable LAS to extract evidence to support or refute the annotations automatically by checking the inter-rule relationships. LAS is the first metabolite annotation tool capable of explaining in natural language (English) the evidence that supports or refutes the annotations. This facilitates the understanding of the results by the user and, thus, increases the user's confidence in the results. Concerning its performance, in an evaluation of blood plasma samples whose compounds had previously been identified using well-established standards, LAS yielded an F-measure higher than 80%.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Espanha