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» Data capture in bioinformatics: requirements and experiences...
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BMCBI
2005
135views more  BMCBI 2005»
13 years 8 months ago
A robust two-way semi-linear model for normalization of cDNA microarray data
Background: Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative e...
Deli Wang, Jian Huang, Hehuang Xie, Liliana Manzel...
BMCBI
2006
130views more  BMCBI 2006»
13 years 8 months ago
Spatial normalization of array-CGH data
Background: Array-based comparative genomic hybridization (array-CGH) is a recently developed technique for analyzing changes in DNA copy number. As in all microarray analyses, no...
Pierre Neuvial, Philippe Hupé, Isabel Brito...
BMCBI
2004
185views more  BMCBI 2004»
13 years 8 months ago
Linear fuzzy gene network models obtained from microarray data by exhaustive search
Background: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome...
Bahrad A. Sokhansanj, J. Patrick Fitch, Judy N. Qu...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
BMCBI
2008
193views more  BMCBI 2008»
13 years 8 months ago
Missing value imputation for microarray gene expression data using histone acetylation information
Background: It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile ...
Qian Xiang, Xianhua Dai, Yangyang Deng, Caisheng H...