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» Describing Semistructured Data
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BMCBI
2010
113views more  BMCBI 2010»
15 years 6 months ago
Use of historic metabolic biotransformation data as a means of anticipating metabolic sites using MetaPrint2D and Bioclipse
Background: Predicting metabolic sites is important in the drug discovery process to aid in rapid compound optimisation. No interactive tool exists and most of the useful tools ar...
Lars Carlsson, Ola Spjuth, Samuel Adams, Robert C....
BMCBI
2007
173views more  BMCBI 2007»
15 years 6 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
FGCS
2006
111views more  FGCS 2006»
15 years 6 months ago
Collaborative data visualization for Earth Sciences with the OptIPuter
Collaborative visualization of large-scale datasets across geographically distributed sites is becoming increasingly important for Earth Sciences. Not only does it enhance our und...
Nut Taesombut, Xinran (Ryan) Wu, Andrew A. Chien, ...
JMLR
2008
168views more  JMLR 2008»
15 years 6 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
TNN
1998
123views more  TNN 1998»
15 years 6 months ago
A general framework for adaptive processing of data structures
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...
Paolo Frasconi, Marco Gori, Alessandro Sperduti