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135
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CEC
2005
IEEE
15 years 9 months ago
Clustering-based approach to identify solutions for the inference of regulatory networks
Abstract- In this paper we address the problem of finding valid solutions for the problem of inferring gene regulatory networks. Different approaches to directly infer the depende...
Christian Spieth, Felix Streichert, Nora Speer, An...
BMCBI
2008
118views more  BMCBI 2008»
15 years 4 months ago
Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...
153
Voted
FUZZIEEE
2007
IEEE
15 years 10 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
ALIFE
2008
15 years 3 months ago
Exploring the Operational Characteristics of Inference Algorithms for Transcriptional Networks by Means of Synthetic Data
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 9 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...