Network analyses in systems biology: new strategies for dealing with biological complexity
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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.
KeywordsNetwork modeling Systems biology Biological networks Representation Mechanistic research strategies
This paper was initiated while the authors were fellows at the Center for Philosophy of Science, University of Pittsburgh. We would like to thank the Center for providing us such a rich environment that was conducive to establishing this collaboration. We also thank three anonymous referees for their critical suggestions. Ingo Brigandt’s work is also supported by the Social Sciences and Humanities Research Council of Canada (Insight Grant 435-2016-0500).
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