Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to: metabolomic applications within man, including pre-clinical and clinical pharmacometabolomics for precision medicine metabolic profiling and fingerprinting metabolite target analysis metabolomic applications within animals, plants and microbes transcriptomics and proteomics in systems biology Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies. Details Concerning the Submission and Publication Procedures: - No Page Charges - No Fees for Online Color Images - Optional Color Images in Print – EUR 950/USD 1150. VAT or local taxes will be added where applicable. - Optional Open Access Publication Fee (APC) - EUR 2480/USD 3140/GBP 2080. VAT or local taxes will be added where applicable.
Metabolomics
Description
Identifiers
ISSN | 1573-3882 |
e-ISSN | 1573-3890 |
DOI | 10.1007/11306.1573-3890 |
Publisher
Springer US
Additional information
Data set: Springer
Articles
Metabolomics > 2019 > 15 > 12 > 1-10
Introduction Relative oxidation of different metabolic substrates in the heart varies both physiologically and pathologically, in order to meet metabolic demands under different circumstances. 13C labelled substrates have become a key tool for studying substrate use—yet an accurate model is required to analyse the complex data produced as these substrates become incorporated into the Krebs cycle....
Metabolomics > 2019 > 15 > 12 > 1-11
Introduction Formononetin (MBHS) and its glycosylated derivative ononin (MBHG), as the major isoflavones, have exhibited the anti-inflammatory impacts on the lipopolysaccharide (LPS)-induced inflammation. Although various researches have focused on interpreting the pharmaceutical activities of MBHG and MBHS, the molecular mechanisms in zebrafish models are still unclear. Objective The purpose of...
Metabolomics > 2019 > 15 > 12 > 1-15
Introduction Metabolomics is increasingly being used in the clinical setting for disease diagnosis, prognosis and risk prediction. Machine learning algorithms are particularly important in the construction of multivariate metabolite prediction. Historically, partial least squares (PLS) regression has been the gold standard for binary classification. Nonlinear machine learning methods such as random...