Differentiating signals to make biological sense - A guide through databases for MS-based non-targeted metabolomics.
Electrophoresis
; 38(18): 2242-2256, 2017 09.
Article
em En
| MEDLINE
| ID: mdl-28426136
ABSTRACT
Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their online ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as identifier assignment, structural assignment and interpretation of results.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Espectrometria de Massas
/
Bases de Dados Factuais
/
Metabolômica
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Electrophoresis
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Espanha