Network analyses in systems biology: new strategies for dealing with biological complexity.

The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strateg...

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Publicado en:Synthese Vol. 195; no. 4; pp. 1751 - 1778
Autores principales: Green, Sara, Şerban, Maria, Scholl, Raphael, Jones, Nicholaos, Brigandt, Ingo, Bechtel, William
Formato: Artículo
Publicado: Springer Nature Apr2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
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        10.1007/s11229-016-1307-6
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        atl: Network analyses in systems biology: new strategies for dealing with biological complexity.
      aug:
        au:
          Green, Sara
          Şerban, Maria
          Scholl, Raphael
          Jones, Nicholaos
          Brigandt, Ingo
          Bechtel, William
        affil:
          University of Copenhagen, Copenhagen, Denmark
          University of Geneva, Geneva, Switzerland
          University of Alabama in Huntsville, Huntsville, USA
          University of California, San Diego, La Jolla, CA, USA
          University of California, San Diego, USA
      su:
        Systems biology
        Biological networks
        Biocomplexity
        Dynamical systems
        Cancer
      sug:
        subj:
          Systems biology
          Biological networks
          Biocomplexity
          Dynamical systems
          Cancer
      keyword:
        Mechanistic research strategies
        Network modeling
        Representation
      ab: The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological complexity.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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