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WABI
2001
Springer
162views Bioinformatics» more  WABI 2001»
13 years 11 months ago
A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites
A central issue in molecular biology is understanding the regulatory mechanisms that control gene expression. The recent flood of genomic and postgenomic data opens the way for co...
Yoseph Barash, Gill Bejerano, Nir Friedman
COLT
2003
Springer
14 years 19 days ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ï¬...
Mehryar Mohri
TIP
2011
162views more  TIP 2011»
13 years 2 months ago
Kernel Maximum Autocorrelation Factor and Minimum Noise Fraction Transformations
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
Allan Aasbjerg Nielsen
RECOMB
2004
Springer
14 years 22 days ago
Application of Kernel Method to Reveal Subtypes of TF Binding Motifs
Transcription factor binding sites often contain several subtypes of sequences that follow not just one but several different patterns. We developed a novel sensitive method based ...
Alexander E. Kel, Yuri Tikunov, Nico Voss, Jü...
NN
2006
Springer
128views Neural Networks» more  NN 2006»
13 years 7 months ago
Topographic map formation of factorized Edgeworth-expanded kernels
We introduce a new learning algorithm for topographic map formation of Edgeworth-expanded Gaussian activation kernels. In order to avoid the rapid increase in kernel parameters, a...
Marc M. Van Hulle