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» Statistical significance in biological sequence analysis
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BMCBI
2004
106views more  BMCBI 2004»
13 years 7 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
IADIS
2008
13 years 9 months ago
Sisa: Seeded Iterative Signature Algorithm for Biclustering Gene Expression Data
One approach to reduce the complexity of the task in the analysis of large scale genome-wide expression is to group the genes showing similar expression patterns into what are cal...
Neelima Gupta, Seema Aggarwal
BMCBI
2010
115views more  BMCBI 2010»
13 years 7 months ago
Integration of multiple data sources to prioritize candidate genes using discounted rating system
Background: Identifying disease gene from a list of candidate genes is an important task in bioinformatics. The main strategy is to prioritize candidate genes based on their simil...
Yongjin Li, Jagdish Chandra Patra
BMCBI
2007
113views more  BMCBI 2007»
13 years 7 months ago
miRAS: a data processing system for miRNA expression profiling study
Background: The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even a...
Feng Tian, Huayue Zhang, Xinyu Zhang, Chi Song, Yo...
BMCBI
2010
135views more  BMCBI 2010»
13 years 7 months ago
Delineation of amplification, hybridization and location effects in microarray data yields better-quality normalization
Background: Oligonucleotide arrays have become one of the most widely used high-throughput tools in biology. Due to their sensitivity to experimental conditions, normalization is ...
Marc Hulsman, Anouk Mentink, Eugene P. van Someren...