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» Multiplicative Background Risk
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111
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BMCBI
2008
98views more  BMCBI 2008»
15 years 19 days ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo
114
Voted
BMCBI
2007
182views more  BMCBI 2007»
15 years 19 days ago
EDISA: extracting biclusters from multiple time-series of gene expression profiles
Background: Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consistin...
Jochen Supper, Martin Strauch, Dierk Wanke, Klaus ...
84
Voted
BMCBI
2010
95views more  BMCBI 2010»
15 years 19 days ago
EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results
Background: Accurate prediction of antigenic epitopes is important for immunologic research and medical applications, but it is still an open problem in bioinformatics. The case f...
Shide Liang, Dandan Zheng, Daron M. Standley, Bo Y...
BMCBI
2010
125views more  BMCBI 2010»
15 years 19 days ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren
105
Voted
BMCBI
2008
125views more  BMCBI 2008»
15 years 19 days ago
A fast algorithm for the multiple genome rearrangement problem with weighted reversals and transpositions
Background: Due to recent progress in genome sequencing, more and more data for phylogenetic reconstruction based on rearrangement distances between genomes become available. Howe...
Martin Bader, Mohamed Ibrahim Abouelhoda, Enno Ohl...