Prediction of biologically significant components from microarray data: Independently Consistent Expression Discriminator (ICED)

Journal article

Open access

Peer reviewed

Rahul Bijlani, YINHE Cheng, David A Pearce, Andrew I Brooks and Mitsunori Ogihara

Bioinformatics (Oxford, England), Vol.19(1), pp.62-70

2003

PMID: 12499294

Abstract

Bacteriology

Biological and medical sciences

Fundamental and applied biological sciences. Psychology

General aspects

Genetics

Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)

Microbiology

url

https://doi.org/10.1093/bioinformatics/19.1.62View

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Citation topics: 1 Clinical & Life Sciences; 1.54 Molecular & Cell Biology - Genetics; 1.54.79 Gene Expression Data
Web Of Science research areas: Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability
ESI research areas: Biology & Biochemistry

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Title: Prediction of biologically significant components from microarray data: Independently Consistent Expression Discriminator (ICED)
Creators: Rahul Bijlani - Department of Computer Science, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States
YINHE Cheng - Department of Computer Science, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States
David A Pearce - Center for Functional Genomics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States
Andrew I Brooks - Center for Functional Genomics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States
Mitsunori Ogihara - Department of Computer Science, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States
Publication Details: Bioinformatics (Oxford, England), Vol.19(1), pp.62-70
Publisher: Oxford University Press
Academic Unit: College of A&S; A&S - Computer Science
Language: English
Resource Type: Journal article
PMID: 12499294
Record Identifier: 991031614766302976