Computational Modeling at the Cell and Tissue Level in Evo-Devo

  • Miquel Marin-RieraEmail author
  • Isaac Salazar-Ciudad
Living reference work entry


Computational models of development integrate empirical knowledge about the dynamics of development, including the interactions at the level of genes, cells, and tissues. These models are capable of predicting the relationship between genotype and phenotype for a specific organ or embryo part, that is, the association of specific genetic differences with specific phenotypic differences. Thus, they can provide insights into the evolution of specific lineages by predicting what phenotypic variation is present at each generation for selection to act on. In this chapter we explain how computational models of development are designed and describe several approaches using them in order to address specific and general questions in evolution. Models of development can be used to infer the range of possible phenotypes for a given organ or structure and predict the genetic and developmental bases of specific evolutionary transitions. By including realistic developmental dynamics in population-based models of evolution, one can assess the effect of a complex relationship between genotype and phenotype on the dynamics of adaptation in populations. Furthermore, when the structure of development is allowed to change by mutation in these models, general patterns in the evolution of the mechanisms of development can be inferred.


Modeling and simulation Genotype-phenotype map Evolution Evo-devo 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Center of Excellence in Experimental and Computational Biology, Institute of BiotechnologyUniversity of HelsinkiHelsinkiFinland
  2. 2.Department of Genetics and MicrobiologyUniversitat Autònoma de BarcelonaBarcelonaSpain

Section editors and affiliations

  • Philipp Mitteröker
    • 1
  1. 1.Department of Theoretical BiologyUniversity of ViennaViennaAustria

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