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» A cluster validity framework for genome expression data
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KES
2008
Springer
13 years 6 months ago
An Algorithm to Assess the Reliability of Hierarchical Clusters in Gene Expression Data
The validation of clusters discovered in bio-molecular data is a central issue in bioinformatics. Recently, stability-based methods have been successfully applied to the analysis o...
Roberto Avogadri, Matteo Brioschi, Francesca Ruffi...
BMCBI
2007
146views more  BMCBI 2007»
13 years 6 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
CSDA
2008
128views more  CSDA 2008»
13 years 6 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2007
176views more  BMCBI 2007»
13 years 6 months ago
Genome Expression Pathway Analysis Tool - Analysis and visualization of microarray gene expression data under genomic, proteomic
Background: Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be use...
Markus Weniger, Julia C. Engelmann, Jörg Schu...
ECML
2006
Springer
13 years 10 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...