@inproceedings{5ece3391bdf94b48b032b21a92ab98a2,
title = "Gene Network Reconstruction Using a Distributed Genetic Algorithm with a Backprop Local Search",
abstract = "With the first draft completion of multiple organism genome sequencing programmes the emphasis is now moving toward a functional understanding of these genes and their network interactions. Microarray technology allows for large-scale gene experimentation. Using this technology it is possible to find the expression levels of genes across different conditions. The use of a genetic algorithm with a backpropagation local searching mechanism to reconstruct gene networks was investigated. This study demonstrates that the distributed genetic algorithm approach shows promise in that the method can infer gene networks that fit test data closely. Evaluating the biological accuracy of predicted networks from currently available test data is not possible. The best that can be achieved is to produce a set of possible networks to pass to a biologist for experimental verification.",
author = "Mark Cumiskey and John Levine and Douglas Armstrong",
year = "2003",
doi = "10.1007/3-540-36605-9_4",
language = "English",
isbn = "978-3-540-00976-4",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "177--181",
editor = "Stefano Cagnoni and Colin Johnson and Juan Cardalda and Elena Marchiori and David Corne and Jean-Arcady Meyer and Jens Gottlieb and Martin Middendorf and Agn{\`e}s Guillot and G{\"u}nther Raidl and Emma Hart",
booktitle = "Applications of Evolutionary Computing",
address = "United Kingdom",
}