title: Selecting biologically informative genes in co-expression networks with a centrality score.
abstract: BACKGROUND
  Measures of node centrality in biological networks are useful to detect genes with critical functional roles. In gene co-expression networks, highly connected genes (i.e., candidate hubs) have been associated with key disease-related pathways. Although different approaches to estimating gene centrality are available, their potential biological relevance in gene co-expression networks deserves further investigation. Moreover, standard measures of gene centrality focus on binary interaction networks, which may not always be suitable in the context of co-expression networks. Here, I also investigate a method that identifies potential biologically meaningful genes based on a weighted connectivity score and indicators of statistical relevance.
  
  
  RESULTS
  The method enables a characterization of the strength and diversity of co-expression associations in the network. It outperformed standard centrality measures by highlighting more biologically informative genes in different gene co-expression networks and biological research domains. As part of the illustration of the gene selection potential of this approach, I present an application case in zebrafish heart regeneration. The proposed technique predicted genes that are significantly implicated in cellular processes required for tissue regeneration after injury.
  
  
  CONCLUSIONS
  A method for selecting biologically informative genes from gene co-expression networks is provided, together with free open software.
authors.affiliation: NorLux Neuro-Oncology Laboratory, Centre de Recherche Public de la Santé (CRP-Santé), Luxembourg, Luxembourg. Francisco.azuaje@crp-sante.lu.
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Azuaje
mesh_terms: D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D006321:Heart / Q000502:physiology*; D009206:Myocardium / Q000378:metabolism; D012038:Regeneration; D015027:Zebrafish / Q000235:genetics* / Q000378:metabolism / Q000502:physiology*