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» Smoothing of Chemical Analysis Data by Neural Networks
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BMCBI
2007
131views more  BMCBI 2007»
13 years 7 months ago
Prediction of peptides observable by mass spectrometry applied at the experimental set level
Background: When proteins are subjected to proteolytic digestion and analyzed by mass spectrometry using a method such as 2D LC MS/MS, only a portion of the proteotypic peptides a...
William S. Sanders, Susan M. Bridges, Fiona M. McC...
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 5 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
NN
2007
Springer
14 years 1 months ago
Impact of Higher-Order Correlations on Coincidence Distributions of Massively Parallel Data
The signature of neuronal assemblies is the higher-order correlation structure of the spiking activity of the participating neurons. Due to the rapid progress in recording technol...
Sonja Grün, Moshe Abeles, Markus Diesmann
ICDAR
2011
IEEE
12 years 7 months ago
Co-training for Handwritten Word Recognition
—To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on...
Volkmar Frinken, Andreas Fischer, Horst Bunke, Ali...
BMCBI
2008
107views more  BMCBI 2008»
13 years 7 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng