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

10.1186/1471-2105-12-S1-S7

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Main Authors:	Han, H, Li, X.-L
Other Authors:	DEPT 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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spelling	sg-nus-scholar.10635-1816432020-10-27T14:49:30Z Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery Han, H Li, X.-L DEPT OF COMPUTER SCIENCE 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 Algorithms Discriminant Analysis Gene Expression Profiling Neoplasms Oligonucleotide Array Sequence Analysis Principal Component Analysis Sensitivity and Specificity Software Tumor Markers, Biological 10.1186/1471-2105-12-S1-S7 BMC Bioinformatics 12 SUPPL. 1 S7 2020-10-27T11:34:12Z 2020-10-27T11:34:12Z 2011 Article Han, H, Li, X.-L (2011). Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery. BMC Bioinformatics 12 (SUPPL. 1) : S7. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2105-12-S1-S7 14712105 https://scholarbank.nus.edu.sg/handle/10635/181643 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ Unpaywall 20201031
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	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 Algorithms Discriminant Analysis Gene Expression Profiling Neoplasms Oligonucleotide Array Sequence Analysis Principal Component Analysis Sensitivity and Specificity Software Tumor Markers, Biological
spellingShingle	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 Algorithms Discriminant Analysis Gene Expression Profiling Neoplasms Oligonucleotide Array Sequence Analysis Principal Component Analysis Sensitivity and Specificity Software Tumor Markers, Biological Han, H Li, X.-L Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
description	10.1186/1471-2105-12-S1-S7
author2	DEPT OF COMPUTER SCIENCE
author_facet	DEPT OF COMPUTER SCIENCE Han, H Li, X.-L
format	Article
author	Han, H Li, X.-L
author_sort	Han, H
title	Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
title_short	Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
title_full	Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
title_fullStr	Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
title_full_unstemmed	Multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
title_sort	multi-resolution independent component analysis for high-performance tumor classification and biomarker discovery
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/181643
_version_	1683425070272217088

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

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