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BMCBI
2007
194views more  BMCBI 2007»
15 years 7 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2008
132views more  BMCBI 2008»
15 years 7 months ago
Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of
Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analys...
Raffaele Giancarlo, Davide Scaturro, Filippo Utro
BMCBI
2010
113views more  BMCBI 2010»
15 years 7 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
153views more  BMCBI 2007»
15 years 7 months ago
Estimating genealogies from linked marker data: a Bayesian approach
Background: Answers to several fundamental questions in statistical genetics would ideally require knowledge of the ancestral pedigree and of the gene flow therein. A few examples...
Dario Gasbarra, Matti Pirinen, Mikko J. Sillanp&au...
BMCBI
2007
138views more  BMCBI 2007»
15 years 6 months ago
A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic
Background: A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk asse...
Aki Vehtari, Ville-Petteri Mäkinen, Pasi Soin...