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	Analisi della Diversità del Microbioma Multi-Omica	Analisi della Diversità del Microbioma Basata su Reti
Campo	Bioinformatica	Bioinformatica
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	2010s–present	2012
Ideatore	Developed collectively; key frameworks by Le Cao et al. (mixOmics, 2017) and Argelaguet et al. (MOFA, 2018)	Faust, Raes, Friedman, Alm and colleagues
Tipo	Integrative computational pipeline	Integrative bioinformatics pipeline
Fonte seminale	Rohart, F., Gautier, B., Singh, A., & Le Cao, K.-A. (2017). mixOmics: An R package for 'omics feature selection and multiple data integration. PLOS Computational Biology, 13(11), e1005752.	Friedman, J., & Alm, E. J. (2012). Inferring correlation networks from genomic survey data. PLoS Computational Biology, 8(9), e1002687.
Alias	multi-omics microbiome profiling, integrated microbiome omics, multi-modal microbiome analysis, microbiome multi-omics integration	microbial co-occurrence network analysis, microbiome network ecology, ecological network-based diversity, NBMDA
Correlati	5	5
Sintesi	Multi-omics microbiome diversity analysis integrates two or more omic data layers — such as metagenomics, metatranscriptomics, metabolomics, and metaproteomics — to characterise both the composition and functional activity of microbial communities. By linking taxonomic diversity metrics with molecular phenotype data, the approach uncovers how community structure translates into ecological and host-relevant functions that no single omic layer can reveal alone.	Network-based microbiome diversity analysis integrates graph-theoretic co-occurrence network inference with classical alpha- and beta-diversity metrics to characterize the structural organization of microbial communities. Rather than treating taxa as independent entities, the method models pairwise microbial associations as edges in a network, enabling identification of keystone taxa, community modules, and ecological interaction patterns that simple diversity indices cannot detect.