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» Selecting maximally informative genes
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BMCBI
2007
110views more  BMCBI 2007»
13 years 7 months ago
Selection of long oligonucleotides for gene expression microarrays using weighted rank-sum strategy
Background: The design of long oligonucleotides for spotted DNA microarrays requires detailed attention to ensure their optimal performance in the hybridization process. The main ...
Guangan Hu, Manuel Llinás, Jingguang Li, Pe...
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
NAR
2000
117views more  NAR 2000»
13 years 7 months ago
The TIGR Gene Indices: reconstruction and representation of expressed gene sequences
Expressed sequence tags (ESTs) have provided a first glimpse of the collection of transcribed sequences in a variety of organisms. However, a careful analysis of this sequence dat...
John Quackenbush, Feng Liang, Ingeborg Holt, Geo P...
BMCBI
2006
156views more  BMCBI 2006»
13 years 7 months ago
GOFFA: Gene Ontology For Functional Analysis - A FDA Gene Ontology Tool for Analysis of Genomic and Proteomic Data
Background: Gene Ontology (GO) characterizes and categorizes the functions of genes and their products according to biological processes, molecular functions and cellular componen...
Hongmei Sun, Hong Fang, Tao Chen, Roger Perkins, W...
BMCBI
2008
166views more  BMCBI 2008»
13 years 7 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf