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BMCBI
2007
89views more  BMCBI 2007»
15 years 4 months ago
msmsEval: tandem mass spectral quality assignment for high-throughput proteomics
Background: In proteomics experiments, database-search programs are the method of choice for protein identification from tandem mass spectra. As amino acid sequence databases grow...
Jason W. H. Wong, Matthew J. Sullivan, Hugh M. Car...
BMCBI
2007
103views more  BMCBI 2007»
15 years 4 months ago
Dynamic simulation of regulatory networks using SQUAD
Background: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncove...
Alessandro Di Cara, Abhishek Garg, Giovanni De Mic...
BMCBI
2006
146views more  BMCBI 2006»
15 years 3 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...
159
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KAIS
2008
221views more  KAIS 2008»
15 years 3 months ago
Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
Kun Zhang, Wei Fan
152
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JMLR
2006
140views more  JMLR 2006»
15 years 3 months ago
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Masashi Sugiyama
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