Identification of Gene Interaction Networks Based on Evolutionary Computation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

Sung Hoon Jung , Kwang-Hyun Cho

ABSTRACT

This paper investigates applying a genetic algorithm and an evolutionary programming for identification of gene interaction networks from gene expression data. To this end, we employ recurrent neural networks to model gene interaction networks and make use of an artificial gene expression data set from literature to validate the proposed approach. We find that the proposed approach using the genetic algorithm and evolutionary programming can result in better parameter estimates compared with the other previous approach. We also find that any a priori knowledge such as zero relations between genes can further help the identification process whenever it is available. More... »

PAGES

428-439

Book

TITLE

Artificial Intelligence and Simulation

ISBN

978-3-540-24476-9
978-3-540-30583-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-30583-5_46

DOI

http://dx.doi.org/10.1007/978-3-540-30583-5_46

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1010770723


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