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» Combined Gene Selection Methods for Microarray Data Analysis
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BMCBI
2007
103views more  BMCBI 2007»
14 years 12 months ago
A comprehensive evaluation of SAM, the SAM R-package and a simple modification to improve its performance
Background: The Significance Analysis of Microarrays (SAM) is a popular method for detecting significantly expressed genes and controlling the false discovery rate (FDR). Recently...
Shunpu Zhang
BMCBI
2006
180views more  BMCBI 2006»
14 years 12 months ago
The Gaggle: An open-source software system for integrating bioinformatics software and data sources
Background: Systems biologists work with many kinds of data, from many different sources, using a variety of software tools. Each of these tools typically excels at one type of an...
Paul T. Shannon, David J. Reiss, Richard Bonneau, ...
BMCBI
2007
176views more  BMCBI 2007»
14 years 12 months ago
The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications
Background: Information resources on the World Wide Web play an indispensable role in modern biology. But integrating data from multiple sources is often encumbered by the need to...
J. Christopher Bare, Paul T. Shannon, Amy K. Schmi...
BMCBI
2006
82views more  BMCBI 2006»
14 years 12 months ago
Transcriptomic response to differentiation induction
Background: Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A com...
G. W. Patton, Robert M. Stephens, I. A. Sidorov, X...
BMCBI
2008
147views more  BMCBI 2008»
14 years 12 months ago
Simple integrative preprocessing preserves what is shared in data sources
Background: Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data ana...
Abhishek Tripathi, Arto Klami, Samuel Kaski