ArticleProcedia computer science2010
Design of a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations.
Article in Procedia computer science, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Evolutionary Design of Gene Networks: Forced Evolution by Genomic Parasites.Parallel processing letters · 2014Article
- Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks.Methods (San Diego, Calif.) · 2013Review
- In silico evolution of gene cooption in pattern-forming gene networks.TheScientificWorldJournal · 2012Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations is proposed. The approach is based on Genetic Algorithms (GA), with new crossover operators especially designed for these purposes. The new operators use local homology between parental strings to preserve building blocks found by the algorithm. The approach exploits the subbasin-portal architecture of the fitness functions suitable for this kind of evolutionary modeling. This architecture is significant for Royal Road class fitness functions. Two real-life Systems Biology problems with such fitness functions are implemented here: evolution of the bacterial promoter rrnPl and of the enhancer of the Drosophila even-skipped gene. The effectiveness of the approach compared to standard GA is demonstrated on several benchmark and real-life tasks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.