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» Semantic Mining and Analysis of Gene Expression Data
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BMCBI
2007
163views more  BMCBI 2007»
13 years 9 months ago
Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approac
Background: Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Resul...
Carmen Pin, Mark Reuter
DAWAK
2005
Springer
14 years 2 months ago
Gene Expression Biclustering Using Random Walk Strategies
A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial rando...
Fabrizio Angiulli, Clara Pizzuti
CINQ
2004
Springer
138views Database» more  CINQ 2004»
14 years 2 months ago
Relevancy in Constraint-Based Subgroup Discovery
This chapter investigates subgroup discovery as a task of constraint-based mining of local patterns, aimed at describing groups of individuals with unusual distributional character...
Nada Lavrac, Dragan Gamberger
BMCBI
2008
102views more  BMCBI 2008»
13 years 9 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
BMCBI
2008
96views more  BMCBI 2008»
13 years 9 months ago
Use of normalization methods for analysis of microarrays containing a high degree of gene effects
Background: High-throughput microarrays are widely used to study gene expression across tissues and developmental stages. Analysis of gene expression data is challenging in these ...
Terri T. Ni, William J. Lemon, Yu Shyr, Tao P. Zho...