| Literature DB >> 27047991 |
Koon-Kiu Yan1, Daifeng Wang1, Anurag Sethi1, Paul Muir2, Robert Kitchen1, Chao Cheng3, Mark Gerstein4.
Abstract
Biological systems are complex. In particular, the interactions between molecular components often form dense networks that, more often than not, are criticized for being inscrutable 'hairballs'. We argue that one way of untangling these hairballs is through cross-disciplinary network comparison-leveraging advances in other disciplines to obtain new biological insights. In some cases, such comparisons enable the direct transfer of mathematical formalism between disciplines, precisely describing the abstract associations between entities and allowing us to apply a variety of sophisticated formalisms to biology. In cases where the detailed structure of the network does not permit the transfer of complete formalisms between disciplines, comparison of mechanistic interactions in systems for which we have significant day-to-day experience can provide analogies for interpreting relatively more abstruse biological networks. Here, we illustrate how these comparisons benefit the field with a few specific examples related to network growth, organizational hierarchies, and the evolution of adaptive systems.Entities:
Year: 2016 PMID: 27047991 PMCID: PMC4817108 DOI: 10.1016/j.cels.2016.02.014
Source DB: PubMed Journal: Cell Syst ISSN: 2405-4712 Impact factor: 10.304