A gene ontology-based microarray gene expression data analysis for diagnosing pseudomyxoma peritonei

2014 IEEE 7th International Workshop on Computational Intelligence and Applications (IWCIA) ◽

10.1109/iwcia.2014.6988083 ◽

2014 ◽

Author(s):

Hideki Katagiri ◽

Takeshi Uno ◽

Kosuke Kato ◽

Hiroaki Kuwano ◽

Kohei Sasaki ◽

...

Keyword(s):

Gene Expression ◽

Gene Ontology ◽

Data Analysis ◽

Gene Expression Data ◽

Pseudomyxoma Peritonei ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Applying gene ontology to microarray gene expression data analysis

2010 International Conference on System Science and Engineering ◽

10.1109/icsse.2010.5551740 ◽

2010 ◽

Author(s):

Andy C. Yang ◽

Hui-Huang Hsu ◽

Ming-Da Lu

Keyword(s):

Gene Expression ◽

Gene Ontology ◽

Data Analysis ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Microarray gene expression data analysis: a beginners guide by Helen C. Causton, John Quackenbush and Alvis Brazma. Blackwell Science, Oxford, UK

Yeast ◽

10.1002/yea.1107 ◽

2004 ◽

Vol 21 (11) ◽

pp. 973-974

Author(s):

Andrew Hayes ◽

David C. Hoyle

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Quantitative Trait Associated Microarray Gene Expression Data Analysis

Molecular Biology and Evolution ◽

10.1093/molbev/msl019 ◽

2006 ◽

Vol 23 (8) ◽

pp. 1558-1573 ◽

Author(s):

Yi Qu ◽

Shizhong Xu

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Quantitative Trait ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Identification of Candidate IDDM Disease Susceptibility Genes in the Idd Regions of NOD Mice by Temporal Microarray Gene Expression Data Analysis

Clinical Immunology ◽

10.1016/j.clim.2007.03.222 ◽

2007 ◽

Vol 123 ◽

pp. S19

Author(s):

Keiichi Kodama ◽

Demi Dang ◽

Claire Holness ◽

Hideyuki Iwai ◽

Mark Hartnett ◽

...

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Disease Susceptibility ◽

Nod Mice ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Microarray Gene Expression Data Analysis: A Beginners Guide. H. C. CAUSTON, J. QUACKENBUSH and A. BRAZMA. Blackwell Publishing. 2003. 160 pages. ISBN 1405106824. Price £34.99 (paperback).

Genetics Research ◽

10.1017/s0016672303216438 ◽

2003 ◽

Vol 82 (2) ◽

pp. 151-152 ◽

Author(s):

STEVEN RUSSELL

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Capturing best practice for microarray gene expression data analysis

Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '03 ◽

10.1145/956750.956797 ◽

2003 ◽

Author(s):

Gregory Piatetsky-Shapiro ◽

Tom Khabaza ◽

Sridhar Ramaswamy

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Best Practice ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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An efficient optimal leaf ordering for hierarchical clustering in microarray gene expression data analysis

Proceedings. 15th International Workshop on Database and Expert Systems Applications, 2004. ◽

10.1109/dexa.2004.1333506 ◽

2004 ◽

Author(s):

J. Zhang ◽

L. Gruenwald

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Hierarchical Clustering ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Microarray Gene Expression Data Analysis: A Beginner’s Guide. By Helen C Causton, John Quackenbush, and , Alvis Brazma. Malden (Massachusetts): Blackwell Publishing. $54.95 (paper). xi + 160 p + 11 pl; ill.; index. ISBN: 1–40510–682–4. 2003.

The Quarterly Review of Biology ◽

10.1086/425782 ◽

2004 ◽

Vol 79 (3) ◽

pp. 308-309 ◽

Author(s):

Stanley F Nelson

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

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Microarray Gene Expression Data Analysis

Microbial Functional Genomics ◽

10.1002/0471647527.ch7 ◽

2005 ◽

pp. 177-206 ◽

Author(s):

Ying Xu

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Microarray Gene

Download Full-text

Applications of Emerging Patterns for Microarray Gene Expression Data Analysis

Encyclopedia of Database Systems ◽

10.1007/978-1-4614-8265-9_5003 ◽

2018 ◽

pp. 131-132

Author(s):

Guozhu Dong ◽

Jinyan Li

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Gene Expression Data ◽

Microarray Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Microarray Gene Expression ◽

Emerging Patterns ◽

Microarray Gene

Download Full-text