PLOS Computational Biology
Public Library of Science (PLoS)
φ-evo: A program to evolve phenotypic models of biological networks
Volume: 14, Issue: 6
DOI 10.1371/journal.pcbi.1006244




Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present φ-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of φ-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. φ-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.φ-evo: A program to evolve phenotypic models of biological networks&author=&keyword=&subject=Research Article,Biology and Life Sciences,Biochemistry,Biochemical Simulations,Biology and Life Sciences,Computational Biology,Biochemical Simulations,Biology and Life Sciences,Evolutionary Biology,Evolutionary Genetics,Biology and Life Sciences,Developmental Biology,Evolutionary Developmental Biology,Biology and Life Sciences,Evolutionary Biology,Evolutionary Developmental Biology,Biology and Life Sciences,Evolutionary Biology,Evolutionary Immunology,Biology and Life Sciences,Genetics,DNA,Operons,Lac Operon,Biology and Life Sciences,Biochemistry,Nucleic Acids,DNA,Operons,Lac Operon,Biology and Life Sciences,Biophysics,Biophysical Simulations,Physical Sciences,Physics,Biophysics,Biophysical Simulations,Biology and Life Sciences,Computational Biology,Biophysical Simulations,Biology and Life Sciences,Genetics,Gene Expression,Biology and Life Sciences,Evolutionary Biology,Evolutionary Processes,Evolutionary Adaptation,