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dc.contributor.authorFernández Rodríguez, José David
dc.contributor.authorVico-Vela, Francisco José 
dc.contributor.authorDoursat, René
dc.date.accessioned2013-12-02T10:27:01Z
dc.date.available2013-12-02T10:27:01Z
dc.date.issued2013-12-02
dc.identifier.urihttp://hdl.handle.net/10630/6706
dc.description.abstractWhile development plays a critical role in the emergence of diversity, its mechanical and chemical actions are considered to be inextricably correlated with genetic control. Since in most extant species the complex growth from zygote to adult organism is orchestrated by a complex gene regulatory network (GRN), the prevalent view is that the evolution of diverse morphologies must result from the evolution of diverse GRN topologies. By contrast, this work focuses on the unique e ect of developmental processes through an abstract model of self-regulated structure without genetic regulation|only modulation of initial conditions. Here, morphologies are generated by a simple evolutionary algorithm searching for the longest instances of unfolding dynamics based on tensegrity graphs. The usual regulatory function of the genome is taken over by physical constraints in the graphs, making morphological diversity a pure product of structural complexi cation. By highlighting the potential of structural development, our model is relevant to both "structuralist" biological models and bio-inspired systems engineering.es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBiología computacionales_ES
dc.subject.otherComputational biologyes_ES
dc.subject.otherEvolutionary developmentes_ES
dc.subject.otherMorphogenesises_ES
dc.subject.otherIndirect encodinges_ES
dc.subject.otherTensegrityes_ES
dc.titleComplex and Diverse Morphologies Can Develop from a Minimal Genomic Modeles_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Informáticaes_ES
dc.relation.eventtitleGenetic and Evolutionary Computation Conference 2012es_ES
dc.relation.eventplaceNew York, USA.es_ES
dc.relation.eventdate2012 / Julyes_ES


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