title: Mining the modular structure of protein interaction networks.
abstract: BACKGROUND
  Cluster-based descriptions of biological networks have received much attention in recent years fostered by accumulated evidence of the existence of meaningful correlations between topological network clusters and biological functional modules. Several well-performing clustering algorithms exist to infer topological network partitions. However, due to respective technical idiosyncrasies they might produce dissimilar modular decompositions of a given network. In this contribution, we aimed to analyze how alternative modular descriptions could condition the outcome of follow-up network biology analysis.
  
  
  METHODS
  We considered a human protein interaction network and two paradigmatic cluster recognition algorithms, namely: the Clauset-Newman-Moore and the infomap procedures. We analyzed to what extent both methodologies yielded different results in terms of granularity and biological congruency. In addition, taking into account Guimera's cartographic role characterization of network nodes, we explored how the adoption of a given clustering methodology impinged on the ability to highlight relevant network meso-scale connectivity patterns.
  
  
  RESULTS
  As a case study we considered a set of aging related proteins and showed that only the high-resolution modular description provided by infomap, could unveil statistically significant associations between them and inter/intra modular cartographic features. Besides reporting novel biological insights that could be gained from the discovered associations, our contribution warns against possible technical concerns that might affect the tools used to mine for interaction patterns in network biology studies. In particular our results suggested that sub-optimal partitions from the strict point of view of their modularity levels might still be worth being analyzed when meso-scale features were to be explored in connection with external source of biological knowledge.
authors: Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and Instituto de Física de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Pabellón 1, Ciudad Universitaria, Buenos Aires, Argentina.
authors: Ariel José
authors: AJ
authors: Berenstein
authors: Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Universitat Pompeu Fabra (UPF), Carrer del Dr. Aiguader, 88, 08003-Barcelona, Spain.
authors: Janet
authors: J
authors: Piñero
authors: Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Universitat Pompeu Fabra (UPF), Carrer del Dr. Aiguader, 88, 08003-Barcelona, Spain.
authors: Laura Inés
authors: LI
authors: Furlong
authors: Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and Instituto de Física de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Pabellón 1, Ciudad Universitaria, Buenos Aires, Argentina; Laboratorio de Biología de Sistemas Integrativa, Fundación Instituto Leloir, Buenos Aires, Argentina.
authors: Ariel
authors: A
authors: Chernomoretz
mesh_terms: D000375:Aging / Q000235:genetics*; D000465:Algorithms; D016000:Cluster Analysis; D057225:Data Mining / Q000706:statistics & numerical data*; D053263:Gene Regulatory Networks; D006801:Humans; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps