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Self-organizing systems form ordered states in space and time spontaneously and without an external template. The patterns are characterized as dissipative structures because their maintenance requires a flow of energy or matter. After introducing a flow of increasing strength into a system at equilibrium, patterns form instantaneously at certain critical values of the flux. In the language of dynamical systems theory the patterns emerge at bifurcation points corresponding to some critical intensity of the flow. At present we know many well-studied examples of self-organizing systems at many time scales and largely different spatial extensions. Examples are the gigantic red spot on Jupiter, cloud patterns in the atmosphere, the Bénard phenomenon in the coffee cup, the Taylor-Cuvette flow, the Belusov-Zhabotinskii reaction, Liesegang rings, and many other nonlinear phenomena. 2 Recent progress in all fields where self-organization is important confirmed the original concepts and, in addition, gave rise to a new formulation of the old paradigms that allows for a distinction of different forms of self-organizing dynamics in physics, chemistry, and biology. We distinguish here three cases that involve different levels of complexity: self-organization of (i) structure, (ii) function, and (iii) intention or seeming purpose. Structural self-organization became a central issue of nonequilibrium dynamics ever since Alan Turing published his seminal work on chemical morphogenesis [1]. Turing suggested a chemical mechanism based on slow diffusion of an activator and fast diffusion of an inhibitor that can lead to spontaneous formation of stable stationary nonequilibrium patterns through diffusion of some key compounds and argued that such a mechanism could be responsible for the formation of biological patterns. It took 20 years before the Turing mechanism was incorporated into a conceptual framework for pattern formation in early embryonic development that results eventually in the patterns we find in adult organisms [2-6]. Activator and inhibitor are thought to represent two \"morphogens,\" leading to short-range activation and long-range inhibition. For a long time no diffusing morphogen was known in developmental biology and, more-After introducing a flow of increasing strength into a system at equilibrium, patterns form instantaneously at certain critical values of the flux.","publication_date":"2007,,","publication_name":"Complexity","grobid_abstract_attachment_id":"79722241"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Nonlinear dynamics from physics to biology","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [11507755]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":79722241,"attachmentType":"pdf"}"><img alt="First page of “Nonlinear dynamics from physics to biology”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/79722241/mini_magick20220128-29451-1h0xk88.png?1643360755" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Nonlinear dynamics from physics to biology</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="11507755" href="https://independent.academia.edu/PSchuster"><img alt="Profile image of Peter Schuster" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/11507755/5025271/5767664/s65_peter.schuster.jpg" />Peter Schuster</a></div><p class="ds-work-card--detail ds2-5-body-sm">2007, Complexity</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":79722241,"attachmentType":"pdf","workUrl":"https://www.academia.edu/69744385/Nonlinear_dynamics_from_physics_to_biology"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":79722241,"attachmentType":"pdf","workUrl":"https://www.academia.edu/69744385/Nonlinear_dynamics_from_physics_to_biology"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="79722241" data-landing_url="https://www.academia.edu/69744385/Nonlinear_dynamics_from_physics_to_biology" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="77766363" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/77766363/On_the_Thermodynamics_of_Self_Organization_in_Dissipative_Systems_Reflections_on_the_Unification_of_Physics_and_Biology">On the Thermodynamics of Self-Organization in Dissipative Systems: Reflections on the Unification of Physics and Biology</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="49851788" href="https://independent.academia.edu/AshwinVaidya">Ashwin Vaidya</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Fluids</p><p class="ds-related-work--abstract ds2-5-body-sm">In this paper, we discuss some well-known experimental observations on self-organization in dissipative systems. The examples range from pure fluid flow, pattern selection in fluid–solid systems to chemical-reaction-induced flocking and aggregation in fluid systems. In each case, self-organization can be seen to be a function of a persistent internal gradient. One goal of this article is to hint at a common theory to explain such phenomena, which often takes the form of the extremum of some thermodynamic quantity, for instance the rate of entropy production. Such variational theories are not new; they have been in existence for decades and gained popularity through the Nobel Prize-winning work of theorists such as Lars Onsager and Ilya Prigogine. The arguments have evolved since then to include systems of higher complexity and for nonlinear systems, though a comprehensive theory remains elusive. The overall attempt is to bring out examples from physics, chemistry, engineering, and b...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"On the Thermodynamics of Self-Organization in Dissipative Systems: Reflections on the Unification of Physics and Biology","attachmentId":85044813,"attachmentType":"pdf","work_url":"https://www.academia.edu/77766363/On_the_Thermodynamics_of_Self_Organization_in_Dissipative_Systems_Reflections_on_the_Unification_of_Physics_and_Biology","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/77766363/On_the_Thermodynamics_of_Self_Organization_in_Dissipative_Systems_Reflections_on_the_Unification_of_Physics_and_Biology"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="88896776" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/88896776/Reaction_Diffusion_Model_as_a_Framework_for_Understanding_Biological_Pattern_Formation">Reaction-Diffusion Model as a Framework for Understanding Biological Pattern Formation</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="12713635" href="https://independent.academia.edu/LAmbrosone">Luigi Ambrosone</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Science, 2010</p><p class="ds-related-work--abstract ds2-5-body-sm">Turing Model Explained The reaction-diffusion (Turing) model is a theoretical model used to explain self-regulated pattern formation in biology. Although many biologists have heard of this model, a better understanding of the concept would aid its application to many research projects and developmental principles. Kondo and Miura (p. 1616 ) now review the reaction-diffusion model. Despite the associated mathematics, the basic idea of the Turing model is relatively easy to understand and relates to morphogen gradients. In addition, user-friendly software makes it easy to understand how a whole variety of patterns can be produced by this simple mechanism.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Reaction-Diffusion Model as a Framework for Understanding Biological Pattern Formation","attachmentId":92793611,"attachmentType":"pdf","work_url":"https://www.academia.edu/88896776/Reaction_Diffusion_Model_as_a_Framework_for_Understanding_Biological_Pattern_Formation","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/88896776/Reaction_Diffusion_Model_as_a_Framework_for_Understanding_Biological_Pattern_Formation"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="87686226" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/87686226/Introduction_Self_organization_in_nonequilibrium_chemical_systems">Introduction: Self-organization in nonequilibrium chemical systems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="33930747" href="https://independent.academia.edu/IrvingEpstein">Irving Epstein</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Chaos: An Interdisciplinary Journal of Nonlinear Science, 2006</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Introduction: Self-organization in nonequilibrium chemical systems","attachmentId":91828292,"attachmentType":"pdf","work_url":"https://www.academia.edu/87686226/Introduction_Self_organization_in_nonequilibrium_chemical_systems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/87686226/Introduction_Self_organization_in_nonequilibrium_chemical_systems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="5837134" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/5837134/Instabilities_and_Information_in_Biological_Organization">Instabilities and Information in Biological Organization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="180697" href="https://binghamton.academia.edu/HowardPattee">Howard H Pattee</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Instabilities and Information in Biological 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href="https://www.academia.edu/104417723/Self_Organization_and_Genomic_Causality_in_Models_of_Morphogenesis">Self-Organization and Genomic Causality in Models of Morphogenesis</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="7656179" href="https://bgu.academia.edu/UteDeichmann">Ute Deichmann</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Entropy</p><p class="ds-related-work--abstract ds2-5-body-sm">The debate about what causes the generation of form and structure in embryological development goes back to antiquity. Most recently, it has focused on the divergent views as to whether the generation of patterns and form in development is a largely self-organized process or is mainly determined by the genome, in particular, complex developmental gene regulatory processes. This paper presents and analyzes pertinent models of pattern formation and form generation in a developing organism in the past and the present, with a special emphasis on Alan Turing’s 1952 reaction–diffusion model. I first draw attention to the fact that Turing’s paper remained, at first, without a noticeable impact on the community of biologists because purely physical–chemical models were unable to explain embryological development and often also simple repetitive patterns. I then show that from the year 2000 and onwards, Turing’s 1952 paper was increasingly cited also by biologists. The model was updated to i...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Self-Organization and Genomic Causality in Models of Morphogenesis","attachmentId":104153506,"attachmentType":"pdf","work_url":"https://www.academia.edu/104417723/Self_Organization_and_Genomic_Causality_in_Models_of_Morphogenesis","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/104417723/Self_Organization_and_Genomic_Causality_in_Models_of_Morphogenesis"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="97005586" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/97005586/Transient_Turing_patterns_in_a_morphogenetic_model">Transient Turing patterns in a morphogenetic model</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="107790232" href="https://independent.academia.edu/naraguisoni">nara guisoni</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Frontiers in Physics</p><p class="ds-related-work--abstract ds2-5-body-sm">One of the most surprising mechanisms to explain the symmetry breaking phenomenon linked to pattern formation is known as Turing instabilities. These patterns are self-organising spatial structures resulting from the interaction of at least two diffusive species in specific conditions. The ideas of Turing have been used extensively in the specialised literature both to explain developmental patterns, as well as synthetic biology design. In the present work we study a previously proposed morphogenetic synthetic circuit consisting of two genes controlled by the same regulatory system. The spatial homogeneous version of this simple model presents a rich phase diagram, since it has a saddle-node bifurcation, spirals and limit cycle. Linear stability analysis and numerical simulations of the complete model allow us to determine the conditions for the development of Turing patterns, as well as transient patterns. We found that the parameter region where Turing patterns are found is much s...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Transient Turing patterns in a morphogenetic model","attachmentId":98747059,"attachmentType":"pdf","work_url":"https://www.academia.edu/97005586/Transient_Turing_patterns_in_a_morphogenetic_model","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/97005586/Transient_Turing_patterns_in_a_morphogenetic_model"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="93832365" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/93832365/Dissipative_structures_in_nature_and_human_systems">Dissipative structures in nature and human systems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="38729559" href="https://independent.academia.edu/ElisaTiezzi">Elisa Tiezzi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Design and Nature IV, 2008</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Dissipative structures in nature and human systems","attachmentId":96460726,"attachmentType":"pdf","work_url":"https://www.academia.edu/93832365/Dissipative_structures_in_nature_and_human_systems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/93832365/Dissipative_structures_in_nature_and_human_systems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="2667340" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/2667340/On_the_dynamics_of_a_forced_reaction_diffusion_model_for_biological_pattern_formation">On the dynamics of a forced reaction-diffusion model for biological pattern formation</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="21545" href="https://fsu.academia.edu/JamesElsner">James Elsner</a></div><p class="ds-related-work--metadata ds2-5-body-xs">1989</p><p class="ds-related-work--abstract ds2-5-body-sm">Abstract Ideas from the theory of dynamical systems are applied in biological pattern formation. 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data-author-id="32972362" href="https://berkeley.academia.edu/WalterFreeman">Walter Freeman</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Biosystems, 2001</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Biocomplexity: adaptive behavior in complex stochastic dynamical systems","attachmentId":44821790,"attachmentType":"pdf","work_url":"https://www.academia.edu/13901096/Biocomplexity_adaptive_behavior_in_complex_stochastic_dynamical_systems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" 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L., 2007, Complexity, self-organization, and emergence at the edge of chaos in life-origin models, Journal of the Washington Academy of Sciences, 2007, 93: (4) 1-20</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1042229" href="https://lifeorigin.academia.edu/DavidAbel">David L Abel</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Abel, D. 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