Anzeige
Erschienen in:
2005 | OriginalPaper | Buchkapitel
Estimating Gene Networks from Expression Data and Binding Location Data via Boolean Networks
verfasst von : Osamu Hirose, Naoki Nariai, Yoshinori Tamada, Hideo Bannai, Seiya Imoto, Satoru Miyano
Erschienen in: Computational Science and Its Applications – ICCSA 2005
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, we propose a computational method for estimating gene networks by the Boolean network model. The Boolean networks have some practical problems in analyzing DNA microarray gene expression data: One is the choice of threshold value for discretization of gene expression data, since expression data take continuous variables. The other problem is that it is often the case that the optimal gene network is not determined uniquely and it is difficult to choose the optimal one from the candidates by using expression data only. To solve these problems, we use the binding location data produced by Lee
et al
.[8] together with expression data and illustrate a strategy to decide the optimal threshold and gene network. To show the effectiveness of the proposed method, we analyze
Saccharomyces cerevisiae
cell cycle gene expression data as a real application.