Construction of Regulatory Boolean Networks Based on Expression Profiles Data Noise

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After while the “Human Genome Project” proposes, the people complete measures the foreword plan after the multi-gene genome team, also starts to change to these genes and their reciprocity function understanding research. Varieties of gene regulation Boolean networks algorithms have been proposed of the gene expression profiles, however, the problem of noise could always be found in creating a Boolean network. Due to gene expression data are always noisy. In this paper, it show that after the Boolean networks logic function are learned from noisy data, some noise in the Boolean function could be restructure Karnaugh Maps. It could find logic relationships between protein and protein and restructure protein logic networks. It find logic relationship among proteins as well as COGs (clusters of orthogous groups) and build the logic network of protein.

Info:

Periodical:

Advanced Materials Research (Volumes 588-589)

Edited by:

Lawrence Lim

Pages:

2046-2050

Citation:

L. Q. Wang et al., "Construction of Regulatory Boolean Networks Based on Expression Profiles Data Noise", Advanced Materials Research, Vols. 588-589, pp. 2046-2050, 2012

Online since:

November 2012

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Price:

$38.00

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DOI: https://doi.org/10.1126/science.1103330