
Simulating domain architecture evolution
Author(s) -
Xiaoyue Cui,
Yifan Xue,
Collin McCormack,
Alejandro Garcés,
Thomas W. Rachman,
Yi Yang,
Maureen Stolzer,
Dannie Durand
Publication year - 2022
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btac242
Subject(s) - computer science , domain (mathematical analysis) , python (programming language) , inference , architecture , theoretical computer science , artificial intelligence , data mining , programming language , mathematics , mathematical analysis , art , visual arts
Simulation is an essential technique for generating biomolecular data with a 'known' history for use in validating phylogenetic inference and other evolutionary methods. On longer time scales, simulation supports investigations of equilibrium behavior and provides a formal framework for testing competing evolutionary hypotheses. Twenty years of molecular evolution research have produced a rich repertoire of simulation methods. However, current models do not capture the stringent constraints acting on the domain insertions, duplications, and deletions by which multidomain architectures evolve. Although these processes have the potential to generate any combination of domains, only a tiny fraction of possible domain combinations are observed in nature. Modeling these stringent constraints on domain order and co-occurrence is a fundamental challenge in domain architecture simulation that does not arise with sequence and gene family simulation.