Paper Info
Title
An extensible software infrastructure for testing the evolutionary consequences of developmental interactions
Abstract
Quantitative genetic models commonly use the additive genetic variance-covariance matrix (G-matrix) of a set of traits to predict evolution in response to selection. However, non-linear interactions between developmental factors underlying the production of traits can produce dramatic changes to the G-matrix. To our knowledge there are no freely available tools for predicting the effect of non-linear interactions on evolutionary dynamics. We have developed a code base and built two models for testing hypotheses about the effects of specific non-linear developmental interactions on trait (co)variances and ultimate evolutionary trajectories.
Year
DOI
Venue
2015
10.1145/2808719.2816837
BCB
Field
DocType
Citations 
Computer science,Trait,Quantitative genetics,Software,Artificial intelligence,Bioinformatics,Evolutionary dynamics,Extensibility,Machine learning
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Elizabeth Brooks100.68
Alison Scoville200.34
Filip Jagodzinski37114.83