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» Combining microarrays and genetic analysis
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GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 7 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
ICTAI
2003
IEEE
14 years 3 months ago
Integrating Microarray Data by Consensus Clustering
With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equ...
Vladimir Filkov, Steven Skiena
BMCBI
2010
105views more  BMCBI 2010»
13 years 10 months ago
Effects of scanning sensitivity and multiple scan algorithms on microarray data quality
Background: Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of ...
Andrew Williams, Errol M. Thomson
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
14 years 4 months ago
Improving the human readability of features constructed by genetic programming
The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming a...
Matthew Smith, Larry Bull
BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
13 years 10 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang