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Evolving Digital Ecological Networks

“It is hard to realize that the living world as we know it is just one among many possibilities” [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e., digital organisms) that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism). Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks) that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved).

 

Fortuna MA, Zaman L, Wagner AP, Ofria C (2013) Evolving Digital Ecological Networks. PLoS Comput Biol 9(3): e1002928. http://dx.doi.org/10.1371/journal.pcbi.1002928

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Using Protein Interaction Networks to Understand Complex Diseases

Recent developments in biotechnology have enabled interrogation of the cell at various levels, leading to many types of "omic" data that provide valuable information on multiple genetic and environmental factors and their interactions. The featured Web extra is a video interview with Mehmet Koyutürk of Case Western Reserve about how biotechnology can track genetic markers to advance cancer research.

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