scholarly article | Q13442814 |
P6179 | Dimensions Publication ID | 1107943224 |
P356 | DOI | 10.1038/S41596-018-0064-Z |
P2888 | exact match | https://scigraph.springernature.com/pub.10.1038/s41596-018-0064-z |
P698 | PubMed publication ID | 30382244 |
P50 | author | Peer Bork | Q7160367 |
Søren Brunak | Q7666528 | ||
Torben Hansen | Q29583803 | ||
Trine Nielsen | Q37392751 | ||
Matej Orešič | Q38591100 | ||
Helle Krogh Pedersen | Q54152846 | ||
Tuulia Hyötyläinen | Q64022752 | ||
Oluf Borbye Pedersen | Q29583849 | ||
P2093 | author name string | Matej Oresic | |
Oluf Pedersen | |||
Torben Hansen | |||
Valborg Gudmundsdottir | |||
S Dusko Ehrlich | |||
Falk Hildebrand | |||
Henrik Bjørn Nielsen | |||
S. Dusko Ehrlich | |||
Trine Nielsen | |||
Helle Krogh Pedersen | |||
Anders Østergaard Petersen | |||
Sofia K Forslund | |||
Sofia K. Forslund | |||
P2860 | cites work | Metabolic reconstruction for metagenomic data and its application to the human microbiome | Q21092513 |
WGCNA: an R package for weighted correlation network analysis | Q21284194 | ||
KEGG: kyoto encyclopedia of genes and genomes | Q24515297 | ||
Metagenomic microbial community profiling using unique clade-specific marker genes | Q24599864 | ||
A framework for human microbiome research | Q24602401 | ||
The Road to Metagenomics: From Microbiology to DNA Sequencing Technologies and Bioinformatics | Q26770644 | ||
The COG database: a tool for genome-scale analysis of protein functions and evolution | Q27936664 | ||
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 | Q29547403 | ||
A metagenome-wide association study of gut microbiota in type 2 diabetes | Q29547726 | ||
KEGG: new perspectives on genomes, pathways, diseases and drugs | Q37556832 | ||
Weighted gene coexpression network analysis: state of the art. | Q37716707 | ||
Interactions between gut microbiota and host metabolism predisposing to obesity and diabetes | Q37827867 | ||
Optimizing the lipidomics workflow for clinical studies--practical considerations. | Q38412114 | ||
Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics | Q38659135 | ||
Leaky gut - concept or clinical entity? | Q38694531 | ||
RTK: efficient rarefaction analysis of large datasets | Q38842640 | ||
Species-function relationships shape ecological properties of the human gut microbiome | Q39296309 | ||
Shotgun metagenomics, from sampling to analysis | Q40045674 | ||
Some Thoughts on Clinical Trials, Especially Problems of Multiplicity | Q40814404 | ||
Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes | Q42207944 | ||
mixOmics: An R package for 'omics feature selection and multiple data integration | Q45846807 | ||
Metabolomics: beyond biomarkers and towards mechanisms | Q46206242 | ||
Quantitative microbiome profiling links gut community variation to microbial load. | Q46260477 | ||
Towards standards for human fecal sample processing in metagenomic studies. | Q46297290 | ||
Microbiome Datasets Are Compositional: And This Is Not Optional. | Q47149781 | ||
Computational Approaches for Integrative Analysis of the Metabolome and Microbiome | Q47164018 | ||
Experimental design and quantitative analysis of microbial community multiomics | Q47168166 | ||
"Evaluating Causality of Gut Microbiota in Obesity and Diabetes in Humans". | Q47198092 | ||
The MetaCyc database of metabolic pathways and enzymes | Q47742233 | ||
The madness of microbiome: Attempting to find consensus "best practice" for 16S microbiome studies. | Q50088075 | ||
Principal component analysis | Q56763826 | ||
Development and Performance of a Gas Chromatography−Time-of-Flight Mass Spectrometry Analysis for Large-Scale Nontargeted Metabolomic Studies of Human Serum | Q56974372 | ||
Liquid Chromatography-Mass Spectrometry (LC-MS)-Based Lipidomics for Studies of Body Fluids and Tissues | Q57012177 | ||
Best practices for analysing microbiomes | Q60547176 | ||
Critical review of reporting of the data analysis step in metabolomics | Q92104710 | ||
The carbohydrate-active enzymes database (CAZy) in 2013 | Q29617118 | ||
Richness of human gut microbiome correlates with metabolic markers | Q29617365 | ||
Inferring correlation networks from genomic survey data | Q30571637 | ||
Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis | Q30573775 | ||
Similarity network fusion for aggregating data types on a genomic scale | Q30742291 | ||
Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. | Q31048490 | ||
Compositional analysis: a valid approach to analyze microbiome high-throughput sequencing data | Q31108768 | ||
WGCNA Application to Proteomic and Metabolomic Data Analysis | Q31155757 | ||
Normalization and microbial differential abundance strategies depend upon data characteristics | Q31169829 | ||
Nonnegative matrix factorization: an analytical and interpretive tool in computational biology | Q33354938 | ||
Data analysis tool for comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry | Q33854611 | ||
MaxBin: an automated binning method to recover individual genomes from metagenomes using an expectation-maximization algorithm | Q34030850 | ||
The human gut microbiome: ecology and recent evolutionary changes | Q34193464 | ||
Gut metagenome in European women with normal, impaired and diabetic glucose control | Q34347521 | ||
The ConsensusPathDB interaction database: 2013 update | Q34473397 | ||
Human gut microbes impact host serum metabolome and insulin sensitivity | Q34534015 | ||
Metagenomic species profiling using universal phylogenetic marker genes | Q35021237 | ||
Specialized metabolites from the microbiome in health and disease | Q35111744 | ||
An integrated catalog of reference genes in the human gut microbiome | Q35201849 | ||
Binning metagenomic contigs by coverage and composition | Q35251310 | ||
Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota | Q35860108 | ||
An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection | Q35922112 | ||
MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities | Q36015586 | ||
KEGG as a reference resource for gene and protein annotation | Q36434599 | ||
Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation | Q36943702 | ||
Country-specific antibiotic use practices impact the human gut resistome | Q36973632 | ||
P407 | language of work or name | English | Q1860 |
P921 | main subject | software framework | Q271680 |
P577 | publication date | 2018-10-31 | |
P1433 | published in | Nature Protocols | Q3337109 |
P1476 | title | A computational framework to integrate high-throughput '-omics' datasets for the identification of potential mechanistic links | |
A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links |
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Q90248344 | Network Medicine in Pathobiology |
Q111148886 | Networks and Graphs Discovery in Metabolomics Data Analysis and Interpretation |
Q91977919 | Persistent Alterations in Plasma Lipid Profiles Before Introduction of Gluten in the Diet Associated With Progression to Celiac Disease |
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