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ID 34947
file
creator
Enomoto, Yumi
Ushijima, Masaru
Miyata, Satoshi
Matsuura, Masaaki
subject
Biological mechanism
Gene-to-gene interrelationships
Epistasis
Multiple pathways
NDC
Medical sciences
abstract
We propose a methodology for constructing an integrated phenotype prediction model that accounts for multiple pathways regulating a targeted phenotype. The method uses multiple prediction models, each expressing a particular pattern of gene-to-gene interrelationship, such as epistasis. We also propose a methodology using Gene Ontology annotations to infer a biological mechanism from the integrated phenotype prediction model. To construct the integrated models, we employed multiple logistic regression models using a two-step learning approach to examine a number of patterns of gene-to-gene interrelationships. We first selected individual prediction models with acceptable goodness of fit, and then combined the models. The resulting integrated model predicts phenotype as a logical sum of predicted results from the individual models. We used published microarray data on neuroblastoma from Ohira et al (2005) for illustration, constructing an integrated model to predict prognosis and infer the biological mechanisms controlling prognosis. Although the resulting integrated model comprised a small number of genes compared to a previously reported analysis of these data, the model demonstrated excellent performance, with an error rate of 0.12 in a validation analysis. Gene Ontology analysis suggested that prognosis of patients with neuroblastoma may be influenced by biological processes such as cell growth, G-protein signaling, phosphoinositide-mediated signaling, alcohol metabolism, glycolysis, neurophysiological processes, and catecholamine catabolism.
journal title
Hiroshima Journal of Medical Sciences
volume
Volume 57
issue
Issue 1
start page
7
end page
15
date of issued
2008-03
publisher
Hiroshima University Medical Press
issn
0018-2052
ncid
language
eng
nii type
Departmental Bulletin Paper
HU type
Departmental Bulletin Papers
DCMI type
text
format
application/pdf
text version
publisher
rights
(c) Hiroshima University Medical Press.
department
Research Institute for Radiation Biology and Medicine
Graduate School of Biomedical Science
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