Determining conserved metabolic biomarkers from a million database queries.
Bioinformatics
; 31(23): 3721-4, 2015 Dec 01.
Article
en En
| MEDLINE
| ID: mdl-26275895
ABSTRACT
MOTIVATION Metabolite databases provide a unique window into metabolome research allowing the most commonly searched biomarkers to be catalogued. Omic scale metabolite profiling, or metabolomics, is finding increased utility in biomarker discovery largely driven by improvements in analytical technologies and the concurrent developments in bioinformatics. However, the successful translation of biomarkers into clinical or biologically relevant indicators is limited. RESULTS:
With the aim of improving the discovery of translatable metabolite biomarkers, we present search analytics for over one million METLIN metabolite database queries. The most common metabolites found in METLIN were cross-correlated against XCMS Online, the widely used cloud-based data processing and pathway analysis platform. Analysis of the METLIN and XCMS common metabolite data has two primary implications these metabolites, might indicate a conserved metabolic response to stressors and, this data may be used to gauge the relative uniqueness of potential biomarkers. AVAILABILITY AND IMPLEMENTATION METLIN can be accessed by logging on to https//metlin.scripps.edu CONTACT siuzdak@scripps.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Metaboloma
/
Metabolómica
Límite:
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2015
Tipo del documento:
Article
País de afiliación:
Estados Unidos