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@ARTICLE{Altenbuchinger:145050,
      author       = {Altenbuchinger, Michael and Weihs, Antoine and Quackenbush,
                      John and Grabe, Hans Jörgen and Zacharias, Helena U},
      title        = {{G}aussian and {M}ixed {G}raphical {M}odels as
                      (multi-)omics data analysis tools.},
      journal      = {Biochimica et biophysica acta / Gene regulatory mechanisms},
      volume       = {1863},
      number       = {6},
      issn         = {1874-9399},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {DZNE-2020-00410},
      pages        = {194418},
      year         = {2020},
      abstract     = {Gaussian 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.},
      subtyp        = {Review Article},
      keywords     = {Gene Regulatory Networks / Genomics / Humans / Metabolomics
                      / Models, Genetic / Models, Statistical / Normal
                      Distribution / Software},
      cin          = {Rostock / Greifswald common},
      ddc          = {610},
      cid          = {I:(DE-2719)6000017},
      pnm          = {344 - Clinical and Health Care Research (POF3-344)},
      pid          = {G:(DE-HGF)POF3-344},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31639475},
      pmc          = {pmc:PMC7166149},
      doi          = {10.1016/j.bbagrm.2019.194418},
      url          = {https://pub.dzne.de/record/145050},
}