Sammenlign metoder

	Netværksbaseret analyse af mikrobiel diversitet	Netværksbaseret berigelsesanalyse af signalveje
Fagområde	Bioinformatik	Bioinformatik
Familie	Process / pipeline	Process / pipeline
Oprindelsesår	2012	2002 (seminal network-scoring concept); matured 2010–2015
Ophavsperson	Faust, Raes, Friedman, Alm and colleagues	Ideker, Ozier, Schwikowski, and Siegel (network-based scoring); extended by Vaske et al. (PARADIGM) and others
Type	Integrative bioinformatics pipeline	Pathway enrichment and network analysis method
Oprindelig kilde	Friedman, J., & Alm, E. J. (2012). Inferring correlation networks from genomic survey data. PLoS Computational Biology, 8(9), e1002687.	Ideker, T., Ozier, O., Schwikowski, B., & Siegel, A. F. (2002). Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics, 18(suppl_1), S233–S240.
Aliasser	microbial co-occurrence network analysis, microbiome network ecology, ecological network-based diversity, NBMDA	network pathway enrichment, network-based enrichment, topology-based pathway analysis, NBPEA
Relaterede	5	1
Resumé	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.	Network-based pathway enrichment analysis integrates molecular interaction networks — protein-protein interactions, signalling graphs, or gene regulatory networks — with omics measurements to identify biological pathways that are coordinately altered in a condition. Unlike classical over-representation or gene-set enrichment approaches that treat pathway genes as independent lists, this family of methods propagates signals across network edges, capturing the topology of interactions and uncovering dysregulated modules that flat-list enrichment would miss.