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000145050 037__ $$aDZNE-2020-00410
000145050 041__ $$aEnglish
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000145050 1001_ $$0P:(DE-HGF)0$$aAltenbuchinger, Michael$$b0$$eCorresponding author
000145050 245__ $$aGaussian and Mixed Graphical Models as (multi-)omics data analysis tools.
000145050 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2020
000145050 264_1 $$2Crossref$$3print$$bElsevier BV$$c2020-06-01
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000145050 520__ $$aGaussian Graphical Models (GGMs) are tools to infer dependencies between biological variables. Popular applications are the reconstruction of gene, protein, and metabolite association networks. GGMs are an exploratory research tool that can be useful to discover interesting relations between genes (functional clusters) or to identify therapeutically interesting genes, but do not necessarily infer a network in the mechanistic sense. Although GGMs are well investigated from a theoretical and applied perspective, important extensions are not well known within the biological community. GGMs assume, for instance, multivariate normal distributed data. If this assumption is violated Mixed Graphical Models (MGMs) can be the better choice. In this review, we provide the theoretical foundations of GGMs, present extensions such as MGMs or multi-class GGMs, and illustrate how those methods can provide insight in biological mechanisms. We summarize several applications and present user-friendly estimation software. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.
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000145050 650_2 $$2MeSH$$aGene Regulatory Networks
000145050 650_2 $$2MeSH$$aGenomics
000145050 650_2 $$2MeSH$$aHumans
000145050 650_2 $$2MeSH$$aMetabolomics
000145050 650_2 $$2MeSH$$aModels, Genetic
000145050 650_2 $$2MeSH$$aModels, Statistical
000145050 650_2 $$2MeSH$$aNormal Distribution
000145050 650_2 $$2MeSH$$aSoftware
000145050 7001_ $$aWeihs, Antoine$$b1
000145050 7001_ $$aQuackenbush, John$$b2
000145050 7001_ $$0P:(DE-2719)2811781$$aGrabe, Hans Jörgen$$b3$$udzne
000145050 7001_ $$aZacharias, Helena U$$b4
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