Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes
Authors
Keywords
Eigenvector metabolite analysis, Linkage analyses, Environment, Enrichment analyses
Journal
Metabolomics
Volume 12, Issue 11, Pages -
Publisher
Springer Nature
Online
2016-09-20
DOI
10.1007/s11306-016-1117-3
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Integrating transcriptomics and metabolomics to characterise the response of Astragalus membranaceus Bge. var. mongolicus (Bge.) to progressive drought stress
- (2016) Xin Jia et al. BMC GENOMICS
- Natural product discovery: past, present, and future
- (2016) Leonard Katz et al. JOURNAL OF INDUSTRIAL MICROBIOLOGY & BIOTECHNOLOGY
- Metabolic and transcriptomic profiling of Streptococcus intermedius during aerobic and anaerobic growth
- (2016) Fan Fei et al. Metabolomics
- Systems Biology Approaches for Host–Fungal Interactions: An Expanding Multi-Omics Frontier
- (2016) Luka Culibrk et al. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY
- Integrative methods for analyzing big data in precision medicine
- (2016) Vladimir Gligorijević et al. PROTEOMICS
- Using “Omics” and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases
- (2016) Eria A. Rebollar et al. Frontiers in Microbiology
- Combined metabolome and transcriptome profiling provides new insights into diterpene biosynthesis in S. pomifera glandular trichomes
- (2015) Fotini A. Trikka et al. BMC GENOMICS
- FlexFlux: combining metabolic flux and regulatory network analyses
- (2015) Lucas Marmiesse et al. BMC Systems Biology
- Ten years of transcriptomics in wild populations: what have we learned about their ecology and evolution?
- (2015) Mariano Alvarez et al. MOLECULAR ECOLOGY
- The application of “-omics” technologies for the classification and identification of animals
- (2015) Michael J. Raupach et al. ORGANISMS DIVERSITY & EVOLUTION
- Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis
- (2015) Meiyappan Lakshmanan et al. PLANT PHYSIOLOGY
- Genome-Wide Transcriptional Profiling and Metabolic Analysis Uncover Multiple Molecular Responses of the Grass Species Lolium perenne Under Low-Intensity Xenobiotic Stress
- (2015) Anne-Antonella Serra et al. Frontiers in Plant Science
- Genome metabolome integrated network analysis to uncover connections between genetic variants and complex traits: an application to obesity
- (2014) B. Valcarcel et al. Journal of the Royal Society Interface
- MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data
- (2014) Alexander Kaever et al. Metabolomics
- Integration of untargeted metabolomics with transcriptomics reveals active metabolic pathways
- (2014) Kyuil Cho et al. Metabolomics
- FlyBase: introduction of the Drosophila melanogaster Release 6 reference genome assembly and large-scale migration of genome annotations
- (2014) G. dos Santos et al. NUCLEIC ACIDS RESEARCH
- Establishment of Quantitative Severity Evaluation Model for Spinal Cord Injury by Metabolomic Fingerprinting
- (2014) Jin Peng et al. PLoS One
- Modules, networks and systems medicine for understanding disease and aiding diagnosis
- (2014) Mika Gustafsson et al. Genome Medicine
- 3Omics: a web-based systems biology tool for analysis, integration and visualization of human transcriptomic, proteomic and metabolomic data
- (2013) Tien-Chueh Kuo et al. BMC Systems Biology
- Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships
- (2013) Ian H McHardy et al. Microbiome
- Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics
- (2012) Warwick B. Dunn et al. Metabolomics
- Layered reward signalling through octopamine and dopamine in Drosophila
- (2012) Christopher J. Burke et al. NATURE
- Integrative Comparative Analyses of Transcript and Metabolite Profiles from Pepper and Tomato Ripening and Development Stages Uncovers Species-Specific Patterns of Network Regulatory Behavior
- (2012) S. Osorio et al. PLANT PHYSIOLOGY
- MassTRIX Reloaded: Combined Analysis and Visualization of Transcriptome and Metabolome Data
- (2012) Brigitte Wägele et al. PLoS One
- What is needed for next-generation ecological and evolutionary genomics?
- (2012) Scott A. Pavey et al. TRENDS IN ECOLOGY & EVOLUTION
- Detection and interpretation of metabolite–transcript coresponses using combined profiling data
- (2011) Henning Redestig et al. BIOINFORMATICS
- Dopamine in Drosophila: setting arousal thresholds in a miniature brain
- (2011) B. Van Swinderen et al. PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
- Genotype-by-Diet Interactions Drive Metabolic Phenotype Variation in Drosophila melanogaster
- (2010) L. K. Reed et al. GENETICS
- Visualization of omics data for systems biology
- (2010) Nils Gehlenborg et al. NATURE METHODS
- Increased Mitochondrial Oxidative Phosphorylation in the Liver Is Associated With Obesity and Insulin Resistance
- (2010) David A. Buchner et al. Obesity
- Integrating multiple 'omics' analysis for microbial biology: application and methodologies
- (2009) W. Zhang et al. MICROBIOLOGY-SGM
- Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
- (2009) Da Wei Huang et al. Nature Protocols
- Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists
- (2008) Da Wei Huang et al. NUCLEIC ACIDS RESEARCH
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started