Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery

10.1186/1471-2105-12-S1-S7

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Bibliographic Details
Main Authors:	Han, H, Li, X.-L
Other Authors:	DEPARTMENT OF COMPUTER SCIENCE
Format:	Article
Published:	2020
Subjects:	Classification algorithm Experimental comparison Feature selection methods Independent component analysis(ICA) Linear discriminant analysis Local feature extraction Nonnegative matrix factorization State-of-the-art algorithms Algorithms Classifiers Diagnosis Diseases Feature extraction Gene expression Independent component analysis Mica Principal component analysis Support vector machines Tumors Bioinformatics Data mining tumor marker algorithm article classification comparative study computer program discriminant analysis DNA microarray gene expression profiling genetics methodology neoplasm principal component analysis sensitivity and specificity Discriminant Analysis Gene Expression Profiling Neoplasms Oligonucleotide Array Sequence Analysis Principal Component Analysis Sensitivity and Specificity Software Tumor Markers, Biological
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/181643
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Institution:	National University of Singapore

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