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BMCBI
2010
126views more  BMCBI 2010»
15 years 2 months ago
A boosting method for maximizing the partial area under the ROC curve
Background: The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function c...
Osamu Komori, Shinto Eguchi
BMCBI
2008
142views more  BMCBI 2008»
15 years 2 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
BMCBI
2008
148views more  BMCBI 2008»
15 years 2 months ago
StAR: a simple tool for the statistical comparison of ROC curves
Background: As in many different areas of science and technology, most important problems in bioinformatics rely on the proper development and assessment of binary classifiers. A ...
Ismael A. Vergara, Tomás Norambuena, Evandr...
BMCBI
2010
117views more  BMCBI 2010»
15 years 2 months ago
Automatic, context-specific generation of Gene Ontology slims
Background: The use of ontologies to control vocabulary and structure annotation has added value to genomescale data, and contributed to the capture and re-use of knowledge across...
Melissa J. Davis, Muhammad Shoaib B. Sehgal, Mark ...
BMCBI
2008
104views more  BMCBI 2008»
15 years 2 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
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