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» Analysis of Variance for Gene Expression Microarray Data
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CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
15 years 5 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
BMCBI
2011
14 years 8 months ago
Tiling array data analysis: a multiscale approach using wavelets
Background: Tiling array data is hard to interpret due to noise. The wavelet transformation is a widely used technique in signal processing for elucidating the true signal from no...
Alexander Karpikov, Joel S. Rozowsky, Mark Gerstei...
160
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BMCBI
2005
201views more  BMCBI 2005»
15 years 1 months ago
Principal component analysis for predicting transcription-factor binding motifs from array-derived data
Background: The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to...
Yunlong Liu, Matthew P. Vincenti, Hiroki Yokota
IDA
2002
Springer
15 years 1 months ago
A framework for modelling virus gene expression data
Short, high-dimensional, Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would b...
Paul Kellam, Xiaohui Liu, Nigel J. Martin, Christi...
CIBCB
2005
IEEE
15 years 7 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao