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CSB
2003
IEEE
153views Bioinformatics» more  CSB 2003»
14 years 20 days ago
Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
Seiya Imoto, Tomoyuki Higuchi, Takao Goto, Kousuke...
ICML
2005
IEEE
14 years 8 months ago
Active learning for sampling in time-series experiments with application to gene expression analysis
Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which ...
Rohit Singh, Nathan Palmer, David K. Gifford, Bonn...
BMCBI
2005
153views more  BMCBI 2005»
13 years 7 months ago
Mining published lists of cancer related microarray experiments: Identification of a gene expression signature having a critical
Background: Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a ...
Giacomo Finocchiaro, Francesco Mancuso, Heiko M&uu...
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 11 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
CIARP
2009
Springer
14 years 1 months ago
Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach
Abstract. An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many appl...
Fabrício Martins Lopes, Evaldo A. de Olivei...