Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method

10.1186/1471-2105-7-S4-S23

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Main Authors:	Li, X.-L, Tan, Y.-C, Ng, S.-K
Other Authors:	DEPT OF COMPUTER SCIENCE
Format:	Article
Published:	2020
Subjects:	Experimental conditions Functional annotation Gene Expression Data Gene function prediction Hier-archical clustering Microarray experiments Prediction performance Simultaneous monitoring Forecasting Gene expression accuracy article cluster analysis controlled study fungal genetics fuzzy system gene expression gene expression profiling gene function genetic analysis genetic heterogeneity mathematical computing microarray analysis prediction quantitative analysis support vector machine algorithm artificial intelligence biological model computer simulation DNA microarray evaluation study fuzzy logic genetics metabolism physiology procedures signal transduction proteome Algorithms Artificial Intelligence Cluster Analysis Computer Simulation Fuzzy Logic Gene Expression Gene Expression Profiling Models, Biological Oligonucleotide Array Sequence Analysis Proteome Signal Transduction
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/178009
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Institution:	National University of Singapore

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spelling	sg-nus-scholar.10635-1780092023-10-31T09:18:08Z Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method Li, X.-L Tan, Y.-C Ng, S.-K DEPT OF COMPUTER SCIENCE Experimental conditions Functional annotation Gene Expression Data Gene function prediction Hier-archical clustering Microarray experiments Prediction performance Simultaneous monitoring Forecasting Gene expression accuracy article cluster analysis controlled study fungal genetics fuzzy system gene expression gene expression profiling gene function genetic analysis genetic heterogeneity mathematical computing microarray analysis prediction quantitative analysis support vector machine algorithm artificial intelligence biological model cluster analysis computer simulation DNA microarray evaluation study fuzzy logic genetics metabolism physiology procedures signal transduction proteome Algorithms Artificial Intelligence Cluster Analysis Computer Simulation Fuzzy Logic Gene Expression Gene Expression Profiling Models, Biological Oligonucleotide Array Sequence Analysis Proteome Signal Transduction 10.1186/1471-2105-7-S4-S23 BMC Bioinformatics 7 SUPPL.4 S23 2020-10-20T04:49:15Z 2020-10-20T04:49:15Z 2006 Article Li, X.-L, Tan, Y.-C, Ng, S.-K (2006). Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method. BMC Bioinformatics 7 (SUPPL.4) : S23. ScholarBank@NUS Repository. https://doi.org/10.1186/1471-2105-7-S4-S23 14712105 https://scholarbank.nus.edu.sg/handle/10635/178009 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	Experimental conditions Functional annotation Gene Expression Data Gene function prediction Hier-archical clustering Microarray experiments Prediction performance Simultaneous monitoring Forecasting Gene expression accuracy article cluster analysis controlled study fungal genetics fuzzy system gene expression gene expression profiling gene function genetic analysis genetic heterogeneity mathematical computing microarray analysis prediction quantitative analysis support vector machine algorithm artificial intelligence biological model cluster analysis computer simulation DNA microarray evaluation study fuzzy logic genetics metabolism physiology procedures signal transduction proteome Algorithms Artificial Intelligence Cluster Analysis Computer Simulation Fuzzy Logic Gene Expression Gene Expression Profiling Models, Biological Oligonucleotide Array Sequence Analysis Proteome Signal Transduction
spellingShingle	Experimental conditions Functional annotation Gene Expression Data Gene function prediction Hier-archical clustering Microarray experiments Prediction performance Simultaneous monitoring Forecasting Gene expression accuracy article cluster analysis controlled study fungal genetics fuzzy system gene expression gene expression profiling gene function genetic analysis genetic heterogeneity mathematical computing microarray analysis prediction quantitative analysis support vector machine algorithm artificial intelligence biological model cluster analysis computer simulation DNA microarray evaluation study fuzzy logic genetics metabolism physiology procedures signal transduction proteome Algorithms Artificial Intelligence Cluster Analysis Computer Simulation Fuzzy Logic Gene Expression Gene Expression Profiling Models, Biological Oligonucleotide Array Sequence Analysis Proteome Signal Transduction Li, X.-L Tan, Y.-C Ng, S.-K Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
description	10.1186/1471-2105-7-S4-S23
author2	DEPT OF COMPUTER SCIENCE
author_facet	DEPT OF COMPUTER SCIENCE Li, X.-L Tan, Y.-C Ng, S.-K
format	Article
author	Li, X.-L Tan, Y.-C Ng, S.-K
author_sort	Li, X.-L
title	Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
title_short	Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
title_full	Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
title_fullStr	Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
title_full_unstemmed	Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
title_sort	systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/178009
_version_	1781792260053008384

Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method

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