title: Dynamic networks reveal key players in aging.
abstract: BACKGROUND
  Because susceptibility to diseases increases with age, studying aging gains importance. Analyses of gene expression or sequence data, which have been indispensable for investigating aging, have been limited to studying genes and their protein products in isolation, ignoring their connectivities. However, proteins function by interacting with other proteins, and this is exactly what biological networks (BNs) model. Thus, analyzing the proteins' BN topologies could contribute to the understanding of aging. Current methods for analyzing systems-level BNs deal with their static representations, even though cells are dynamic. For this reason, and because different data types can give complementary biological insights, we integrate current static BNs with aging-related gene expression data to construct dynamic age-specific BNs. Then, we apply sensitive measures of topology to the dynamic BNs to study cellular changes with age.
  
  
  RESULTS
  While global BN topologies do not significantly change with age, local topologies of a number of genes do. We predict such genes to be aging-related. We demonstrate credibility of our predictions by (i) observing significant overlap between our predicted aging-related genes and 'ground truth' aging-related genes; (ii) observing significant overlap between functions and diseases that are enriched in our aging-related predictions and those that are enriched in 'ground truth' aging-related data; (iii) providing evidence that diseases which are enriched in our aging-related predictions are linked to human aging; and (iv) validating our high-scoring novel predictions in the literature.
  
  
  METHODS
  Software executables are available upon request.
authors.affiliation: Department of Computer Science and Engineering, ECK Institute for Global Health and Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN 46556, USA.
authors.forename: Fazle E
authors.initials: FE
authors.lastname: Faisal
authors.affiliation: Department of Computer Science and Engineering, ECK Institute for Global Health and Interdisciplinary Center for Network Science and Applications, University of Notre Dame, Notre Dame, IN 46556, USA.
authors.forename: Tijana
authors.initials: T
authors.lastname: Milenković
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000235:genetics / Q000378:metabolism*; D020869:Gene Expression Profiling; D063990:Gene Ontology; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D025941:Protein Interaction Mapping; D055815:Young Adult