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BMCBI
2008
169views more  BMCBI 2008»
14 years 10 months ago
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
Background: Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular sig...
Alexander R. Statnikov, Lily Wang, Constantin F. A...
BMCBI
2007
106views more  BMCBI 2007»
14 years 10 months ago
Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logari
Background: Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend up...
Helen M. Parsons, Christian Ludwig, Ulrich L. G&uu...
ACMSE
2009
ACM
15 years 4 months ago
Applying randomized projection to aid prediction algorithms in detecting high-dimensional rogue applications
This paper describes a research effort to improve the use of the cosine similarity information retrieval technique to detect unknown, known or variances of known rogue software by...
Travis Atkison
IJON
2008
128views more  IJON 2008»
14 years 9 months ago
Independent arrays or independent time courses for gene expression time series data analysis
In this paper we apply three different independent component analysis (ICA) methods, including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to gene exp...
Sookjeong Kim, Jong Kyoung Kim, Seungjin Choi
BMCBI
2004
205views more  BMCBI 2004»
14 years 9 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma