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BMCBI
2006
201views more  BMCBI 2006»
13 years 10 months ago
Gene selection algorithms for microarray data based on least squares support vector machine
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
BMCBI
2010
130views more  BMCBI 2010»
13 years 10 months ago
Knowledge-guided gene ranking by coordinative component analysis
Background: In cancer, gene networks and pathways often exhibit dynamic behavior, particularly during the process of carcinogenesis. Thus, it is important to prioritize those gene...
Chen Wang, Jianhua Xuan, Huai Li, Yue Wang, Ming Z...
BMCBI
2011
13 years 4 months ago
Appearance frequency modulated gene set enrichment testing
Background: Gene set enrichment testing has helped bridge the gap from an individual gene to a systems biology interpretation of microarray data. Although gene sets are defined a ...
Jun Ma, Maureen A. Sartor, H. V. Jagadish
BMCBI
2006
94views more  BMCBI 2006»
13 years 10 months ago
Noise-injected neural networks show promise for use on small-sample expression data
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
BMCBI
2010
190views more  BMCBI 2010»
13 years 10 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...