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BMCBI
2007
77views more  BMCBI 2007»
13 years 7 months ago
Effective selection of informative SNPs and classification on the HapMap genotype data
Background: Since the single nucleotide polymorphisms (SNPs) are genetic variations which determine the difference between any two unrelated individuals, the SNPs can be used to i...
Nina Zhou, Lipo Wang
BMCBI
2004
176views more  BMCBI 2004»
13 years 7 months ago
Boosting accuracy of automated classification of fluorescence microscope images for location proteomics
Background: Detailed knowledge of the subcellular location of each expressed protein is critical to a full understanding of its function. Fluorescence microscopy, in combination w...
Kai Huang, Robert F. Murphy
TKDE
2010
182views more  TKDE 2010»
13 years 6 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
KDD
2005
ACM
130views Data Mining» more  KDD 2005»
14 years 8 months ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi