http://swrc.ontoware.org/ontology#TechnicalReport
Network Completion for Static Gene Expression Data
en
Bioinformatics Center, Institute for Chemical Research, Kyoto University
Bioinformatics Center, Institute for Chemical Research, Kyoto University
Natsu Nakajima
Tatsuya Akutsu
In this report, we address the problem of completing and inferring gene regulatory networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which additions and deletions of edges are basic modification operations. For this problem, we present a novel method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data and microarray data from normal lung and lung cancer tissue samples.
In this report, we address the problem of completing and inferring gene regulatory networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which additions and deletions of edges are basic modification operations. For this problem, we present a novel method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data and microarray data from normal lung and lung cancer tissue samples.
AA12055912
研究報告バイオ情報学（BIO）
2015-BIO-41
7
1-4
2015-03-13