Classification of genes based on gene expression analysis
Abstract
Systems biology and bioinformatics are now major fields for productive research. DNA microarrays and other array technologies and genome sequencing have advanced to the point that it is now possible to monitor gene expression on a genomic scale. Gene expression analysis is discussed and some important clustering techniques are considered. The patterns identified in the data suggest similarities in the gene behavior, which provides useful information for the gene functionalities. We discuss measures for investigating the homogeneity of gene expression data in order to optimize the clustering process. We contribute to the knowledge of functional roles and regulation of E. coli genes by proposing a classification of these genes based on consistently correlated genes in expression data and similarities of gene expression patterns. A new visualization tool for targeted projection pursuit and dimensionality reduction of gene expression data is demonstrated.
- Authors:
-
- Northumbria University (United Kingdom)
- Publication Date:
- OSTI Identifier:
- 21402595
- Resource Type:
- Journal Article
- Journal Name:
- Physics of Atomic Nuclei
- Additional Journal Information:
- Journal Volume: 71; Journal Issue: 5; Other Information: DOI: 10.1134/S1063778808050025; Copyright (c) 2008 Pleiades Publishing, Ltd.; Journal ID: ISSN 1063-7788
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; BIOLOGY; CLASSIFICATION; DNA; GENES; NUCLEIC ACIDS; ORGANIC COMPOUNDS
Citation Formats
Angelova, M, Myers, C, and Faith, J. Classification of genes based on gene expression analysis. United States: N. p., 2008.
Web. doi:10.1134/S1063778808050025.
Angelova, M, Myers, C, & Faith, J. Classification of genes based on gene expression analysis. United States. https://doi.org/10.1134/S1063778808050025
Angelova, M, Myers, C, and Faith, J. 2008.
"Classification of genes based on gene expression analysis". United States. https://doi.org/10.1134/S1063778808050025.
@article{osti_21402595,
title = {Classification of genes based on gene expression analysis},
author = {Angelova, M and Myers, C and Faith, J},
abstractNote = {Systems biology and bioinformatics are now major fields for productive research. DNA microarrays and other array technologies and genome sequencing have advanced to the point that it is now possible to monitor gene expression on a genomic scale. Gene expression analysis is discussed and some important clustering techniques are considered. The patterns identified in the data suggest similarities in the gene behavior, which provides useful information for the gene functionalities. We discuss measures for investigating the homogeneity of gene expression data in order to optimize the clustering process. We contribute to the knowledge of functional roles and regulation of E. coli genes by proposing a classification of these genes based on consistently correlated genes in expression data and similarities of gene expression patterns. A new visualization tool for targeted projection pursuit and dimensionality reduction of gene expression data is demonstrated.},
doi = {10.1134/S1063778808050025},
url = {https://www.osti.gov/biblio/21402595},
journal = {Physics of Atomic Nuclei},
issn = {1063-7788},
number = 5,
volume = 71,
place = {United States},
year = {Thu May 15 00:00:00 EDT 2008},
month = {Thu May 15 00:00:00 EDT 2008}
}