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Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity

Green, Sara and Serban, Maria and Scholl, Raphael and Jones, Nicholaos and Brigandt, Ingo and Bechtel, William (2016) Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity. [Preprint]

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Abstract

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.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Green, Sarasaraehrenreichgreen@gmail.com
Serban, Mariamariaserban.org@gmail.com
Scholl, Raphaelraphael.scholl@gmail.com
Jones, Nicholaosnick.jones@uah.edu
Brigandt, Ingobrigandt@ualberta.ca
Bechtel, Williambill@mechanism.ucsd.edu
Additional Information: Preprint of a paper forthcoming in Synthese
Keywords: networks, mechanisms, modeling, analytical strategies, representational strategies, systems biology
Subjects: Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Models and Idealization
Depositing User: Ingo Brigandt
Date Deposited: 24 Dec 2016 00:30
Last Modified: 24 Dec 2016 00:30
Item ID: 12715
Subjects: Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Models and Idealization
Date: 19 December 2016
URI: https://philsci-archive.pitt.edu/id/eprint/12715

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