Integration of metabolomics, lipidomics and clinical data using a machine learning method
Abstract Background The recent pandemic of obesity and the metabolic syndrome (MetS) has led to the realisation that new drug targets are needed to either reduce obesity or the subsequent pathophysiological consequences associated with excess weight gain. Certain nuclear hormone receptors (NRs) play...
Main Authors: | Animesh Acharjee, Zsuzsanna Ament, James A. West, Elizabeth Stanley, Julian L. Griffin |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2016-11-01
|
Series: | BMC Bioinformatics |
Online Access: | http://link.springer.com/article/10.1186/s12859-016-1292-2 |
Similar Items
-
Enantioselectivity Effects in Clinical Metabolomics and Lipidomics
by: Regina V. Oliveira, et al.
Published: (2021-08-01) -
Metabolomics dataset of PPAR-pan treated rat liver
by: Zsuzsanna Ament, et al.
Published: (2016-09-01) -
A resource of lipidomics and metabolomics data from individuals with undiagnosed diseases
by: Jennifer E. Kyle, et al.
Published: (2021-04-01) -
Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer
by: Vartika Bisht, et al.
Published: (2021-05-01) -
Comparative Metabolomic and Lipidomic Analysis of Phenotype Stratified Prostate Cells.
by: Tanya C Burch, et al.
Published: (2015-01-01)