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» Selecting maximally informative genes
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BMCBI
2004
206views more  BMCBI 2004»
13 years 7 months ago
Combining gene expression data from different generations of oligonucleotide arrays
Background: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public re...
Kyu Baek Hwang, Sek Won Kong, Steven A. Greenberg,...
BMCBI
2008
114views more  BMCBI 2008»
13 years 7 months ago
WSPMaker: a web tool for calculating selection pressure in proteins and domains using window-sliding
Background: In the study of adaptive evolution, it is important to detect the protein coding sites where natural selection is acting. In general, the ratio of the rate of non-syno...
Yong Seok Lee, Tae-Hyung Kim, Tae-Wook Kang, Won-H...
JMLR
2006
89views more  JMLR 2006»
13 years 7 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
BMCBI
2005
141views more  BMCBI 2005»
13 years 7 months ago
Construction and validation of the APOCHIP, a spotted oligo-microarray for the study of beta-cell apoptosis
Background: Type 1 diabetes mellitus (T1DM) is a autoimmune disease caused by a long-term negative balance between immune-mediated beta-cell damage and beta-cell repair/regenerati...
Nils E. Magnusson, Alessandra K. Cardozo, Mogens K...
ICML
2005
IEEE
14 years 8 months ago
Active learning for sampling in time-series experiments with application to gene expression analysis
Many time-series experiments seek to estimate some signal as a continuous function of time. In this paper, we address the sampling problem for such experiments: determining which ...
Rohit Singh, Nathan Palmer, David K. Gifford, Bonn...