| Item type |
デフォルトアイテムタイプ_（フル）(1) |
| 公開日 |
2023-03-18 |
| タイトル |
|
|
タイトル |
Inference on Biological Mechanisms Using an Integrated Phenotype Prediction Model |
|
言語 |
en |
| 作成者 |
Enomoto, Yumi
Ushijima, Masaru
Miyata, Satoshi
Matsuura, Masaaki
Ohtaki, Megu
|
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利情報 |
|
|
権利情報 |
(c) Hiroshima University Medical Press. |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
Biological mechanism |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
Gene-to-gene interrelationships |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
Epistasis |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
Multiple pathways |
| 主題 |
|
|
主題Scheme |
NDC |
|
主題 |
490 |
| 内容記述 |
|
|
内容記述 |
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. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
Hiroshima University Medical Press |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
departmental bulletin paper |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 収録物識別子 |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
0018-2052 |
| 収録物識別子 |
|
|
収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA00664312 |
| 開始ページ |
|
|
開始ページ |
7 |
| 書誌情報 |
Hiroshima Journal of Medical Sciences
Hiroshima Journal of Medical Sciences
巻 57,
号 1,
p. 7-15,
発行日 2008-03
|
| 旧ID |
34947 |
HiroshimaJMedSci_57_7.pdf (7.2 MB)
