title: Deciphering hallmark processes of aging from interaction networks.
abstract: Aging is broadly considered to be a dynamic process that accumulates unfavourable structural and functional changes in a time dependent fashion, leading to a progressive loss of physiological integrity of an organism, which eventually leads to age-related diseases and finally to death.
  
  
  
  The majority of aging-related studies are based on reductionist approaches, focusing on single genes/proteins or on individual pathways without considering possible interactions between them. Over the last few decades, several such genes/proteins were independently analysed and linked to a role that is affecting the longevity of an organism. However, an isolated analysis on genes and proteins largely fails to explain the mechanistic insight of a complex phenotype due to the involvement and integration of multiple factors.
  
  
  
  Technological advance makes it possible to generate high-throughput temporal and spatial data that provide an opportunity to use computer-based methods. These techniques allow us to go beyond reductionist approaches to analyse large-scale networks that provide deeper understanding of the processes that drive aging.
  
  
  
  In this review, we focus on systems biology approaches, based on network inference methods to understand the dynamics of hallmark processes leading to aging phenotypes. We also describe computational methods for the interpretation and identification of important molecular hubs involved in the mechanistic linkage between aging related processes. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.
authors.affiliation: Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany; Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany. Electronic address: suchi.smita@uni-rostock.de.
authors.forename: Suchi
authors.initials: S
authors.lastname: Smita
authors.affiliation: Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany. Electronic address: falko.lange@uni-rostock.de.
authors.forename: Falko
authors.initials: F
authors.lastname: Lange
authors.affiliation: Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany; Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa. Electronic address: olaf.wolkenhauer@uni-rostock.de.
authors.forename: Olaf
authors.initials: O
authors.lastname: Wolkenhauer
authors.affiliation: Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany. Electronic address: ruediger.koehling@uni-rostock.de.
authors.forename: Rüdiger
authors.initials: R
authors.lastname: Köhling
mesh_terms: D000375:Aging / Q000235:genetics*; D000818:Animals; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D008136:Longevity / Q000235:genetics; D010641:Phenotype; D049490:Systems Biology
keywords: Aging; Data integration; Network inference; Systems biology; Target hubs