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» Comparing transformation methods for DNA microarray data
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122
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BMCBI
2006
137views more  BMCBI 2006»
15 years 2 months ago
Biologically relevant effects of mRNA amplification on gene expression profiles
Background: Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies an...
Rachel I. M. van Haaften, Blanche Schroen, Ben J. ...
ICMLA
2007
15 years 3 months ago
Machine learned regression for abductive DNA sequencing
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
David Thornley, Maxim Zverev, Stavros Petridis
BMCBI
2010
50views more  BMCBI 2010»
15 years 2 months ago
Scanner calibration revisited
Background: Calibration of a microarray scanner is critical for accurate interpretation of microarray results. Shi et al. (BMC Bioinformatics, 2005, 6, Art. No. S11 Suppl. 2.) rep...
Alexander E. Pozhitkov
PRICAI
2004
Springer
15 years 7 months ago
Prediction of the Risk Types of Human Papillomaviruses by Support Vector Machines
Abstract. Infection by high-risk human papillomaviruses (HPVs) is associated with the development of cervical cancers. Classification of risk types is important to understand the ...
Je-Gun Joung, Sok June Oh, Byoung-Tak Zhang
128
Voted
CIBCB
2006
IEEE
15 years 8 months ago
A Model-Free Greedy Gene Selection for Microarray Sample Class Prediction
— Microarray data analysis is notoriously challenging as it involves a huge number of genes compared to only a limited number of samples. Gene selection, to detect the most signi...
Yi Shi, Zhipeng Cai, Lizhe Xu, Wei Ren, Randy Goeb...