Paper Info
Title
Finding the minimal gene regulatory function in the presence of undefined transitional states using a genetic algorithm
Abstract
After the sequencing of whole genomes and the identification of the genes contained in them, one of the main challenges remaining is to understand the mechanisms that regulate the expression of genes within the genome in order to gain knowledge about structural, biochemical, physiological and behavioral characteristics of organisms. Some of these mechanisms are controlled by so-called Genetic Regulatory Networks (GRNs). Boolean networks can help model biological GRNs. In this paper, a genetic algorithm is used to make inferences in Boolean networks, in combination with the Quine-McCluskey algorithm, when not all the output states of the genes have been determined. This lack of information could be treated as "don't care" states. Genetic algorithms are useful in multi-objective optimization problems, such as minimization of Gene Regulatory Functions, where it is important not only to have the smallest quantity of disjunctions, but also the smallest quantity of genes involved in the regulation.
Year
DOI
Venue
2012
10.1007/978-3-642-28792-3_29
IPCAT
Keywords
Field
DocType
minimal gene,genetic algorithm,boolean network,model biological grns,gene regulatory functions,regulatory function,smallest quantity,behavioral characteristic,multi-objective optimization problem,quine-mccluskey algorithm,so-called genetic regulatory networks,undefined transitional state,main challenge,quine mccluskey algorithm
Genome,Gene,Biology,Algorithm,Quine–McCluskey algorithm,Computational biology,Optimization problem,Genetic algorithm
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Rocio Chavez-Alvarez100.34
Arturo Chavoya2728.42
Cuauhtémoc López-Martín38611.13