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      The Comet Cometh: Evolving Developmental Systems

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          Abstract

          In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule’s prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach—which is based on reverse engineering, simulation, and mathematical analysis—the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

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          Nothing in Biology Makes Sense except in the Light of Evolution

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            Modeling and simulation of genetic regulatory systems: a literature review.

            In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between DNA, RNA, proteins, and small molecules. As most genetic regulatory networks of interest involve many components connected through interlocking positive and negative feedback loops, an intuitive understanding of their dynamics is hard to obtain. As a consequence, formal methods and computer tools for the modeling and simulation of genetic regulatory networks will be indispensable. This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations, ordinary and partial differential equations, qualitative differential equations, stochastic equations, and rule-based formalisms. In addition, the paper discusses how these formalisms have been used in the simulation of the behavior of actual regulatory systems.
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              Reaction-diffusion model as a framework for understanding biological pattern formation.

              The Turing, or reaction-diffusion (RD), model is one of the best-known theoretical models used to explain self-regulated pattern formation in the developing animal embryo. Although its real-world relevance was long debated, a number of compelling examples have gradually alleviated much of the skepticism surrounding the model. The RD model can generate a wide variety of spatial patterns, and mathematical studies have revealed the kinds of interactions required for each, giving this model the potential for application as an experimental working hypothesis in a wide variety of morphological phenomena. In this review, we describe the essence of this theory for experimental biologists unfamiliar with the model, using examples from experimental studies in which the RD model is effectively incorporated.
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                Author and article information

                Contributors
                yogi.jaeger@crg.eu
                Journal
                Biol Theory
                Biol Theory
                Biological Theory
                Springer Netherlands (Dordrecht )
                1555-5542
                1555-5550
                17 February 2015
                17 February 2015
                2015
                : 10
                : 1
                : 36-49
                Affiliations
                [ ]EMBL/CRG Research Unit in Systems Biology, Centre for Genomic Regulation (CRG), Barcelona, Spain
                [ ]Universitat Pompeu Fabra, Barcelona, Spain
                [ ]Wissenschaftskolleg zu Berlin, Berlin, Germany
                [ ]School of Life Sciences, Arizona State University, Tempe, AZ USA
                [ ]Santa Fe Institute, Santa Fe, NM USA
                [ ]Marine Biological Laboratory, Woods Hole, MA USA
                [ ]Max Planck Institute for the History of Science, Berlin, Germany
                [ ]The KLI Institute, Klosterneuburg, Austria
                Article
                203
                10.1007/s13752-015-0203-5
                4357653
                25798078
                4a7ef62e-3c05-4499-8daa-696f96b280f5
                © The Author(s) 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

                History
                : 18 January 2015
                : 27 January 2015
                Categories
                Thematic Section Article: Evolutionary Systems Biology
                Custom metadata
                © Konrad Lorenz Institute for Evolution and Cognition Research 2015

                Comparative biology
                dynamical systems theory,epistemology,evolutionary developmental biology (evodevo),evolutionary systems biology,natural history of configuration space,scientific perspectivism

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