Mapping physiological states from microarray expression measurements

Gregory Stephanopoulos, Daehee Hwang, William A. Schmitt, Jatin Misra, George Stephanopoulos

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

Motivation: The increasing use of DNA microarrays to probe cell physiology requires methods for visualizing different expression phenotypes and explicitly connecting individual genes to discriminating expression features. Such methods should be robust and maintain biological interpretability. Results: We propose a method for the mapping of the physiological state of cells and tissues from multidimensional expression data such as those obtained with DNA microarrays. The method uses Fisher discriminant analysis to create a linear projection of gene expression measurements that maximizes the separation of different sample classes. Relative to other typical classification methods, this method provides insights into the discriminating characteristics of expression measurements in terms of the contribution of individual genes to the definition of distinct physiological states. This projection method also facilitates visualization of classification results in a reduced dimensional space. Examples from four different cases demonstrate the ability of the method to produce well-separated groups in the projection space and to identify important genes for defining physiological states. The method can be augmented to also include data from the proteomic and metabolic phenotypes and can be useful in disease diagnosis, drug screening and bioprocessing applications.

Original languageEnglish (US)
Pages (from-to)1054-1063
Number of pages10
JournalBioinformatics
Volume18
Issue number8
DOIs
StatePublished - Jan 1 2002
Externally publishedYes

Fingerprint

Microarrays
Microarray
Genes
DNA
Physiology
Discriminant analysis
Gene expression
DNA Microarray
Screening
Visualization
Gene
Phenotype
Tissue
Oligonucleotide Array Sequence Analysis
Fisher Discriminant Analysis
Linear Projection
Pharmaceutical Preparations
Cell Physiological Phenomena
Interpretability
Proteomics

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Mapping physiological states from microarray expression measurements. / Stephanopoulos, Gregory; Hwang, Daehee; Schmitt, William A.; Misra, Jatin; Stephanopoulos, George.

In: Bioinformatics, Vol. 18, No. 8, 01.01.2002, p. 1054-1063.

Research output: Contribution to journalArticle

Stephanopoulos, Gregory ; Hwang, Daehee ; Schmitt, William A. ; Misra, Jatin ; Stephanopoulos, George. / Mapping physiological states from microarray expression measurements. In: Bioinformatics. 2002 ; Vol. 18, No. 8. pp. 1054-1063.
@article{1ef33443862f41869cfda0e820623645,
title = "Mapping physiological states from microarray expression measurements",
abstract = "Motivation: The increasing use of DNA microarrays to probe cell physiology requires methods for visualizing different expression phenotypes and explicitly connecting individual genes to discriminating expression features. Such methods should be robust and maintain biological interpretability. Results: We propose a method for the mapping of the physiological state of cells and tissues from multidimensional expression data such as those obtained with DNA microarrays. The method uses Fisher discriminant analysis to create a linear projection of gene expression measurements that maximizes the separation of different sample classes. Relative to other typical classification methods, this method provides insights into the discriminating characteristics of expression measurements in terms of the contribution of individual genes to the definition of distinct physiological states. This projection method also facilitates visualization of classification results in a reduced dimensional space. Examples from four different cases demonstrate the ability of the method to produce well-separated groups in the projection space and to identify important genes for defining physiological states. The method can be augmented to also include data from the proteomic and metabolic phenotypes and can be useful in disease diagnosis, drug screening and bioprocessing applications.",
author = "Gregory Stephanopoulos and Daehee Hwang and Schmitt, {William A.} and Jatin Misra and George Stephanopoulos",
year = "2002",
month = "1",
day = "1",
doi = "10.1093/bioinformatics/18.8.1054",
language = "English (US)",
volume = "18",
pages = "1054--1063",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "8",

}

TY - JOUR

T1 - Mapping physiological states from microarray expression measurements

AU - Stephanopoulos, Gregory

AU - Hwang, Daehee

AU - Schmitt, William A.

AU - Misra, Jatin

AU - Stephanopoulos, George

PY - 2002/1/1

Y1 - 2002/1/1

N2 - Motivation: The increasing use of DNA microarrays to probe cell physiology requires methods for visualizing different expression phenotypes and explicitly connecting individual genes to discriminating expression features. Such methods should be robust and maintain biological interpretability. Results: We propose a method for the mapping of the physiological state of cells and tissues from multidimensional expression data such as those obtained with DNA microarrays. The method uses Fisher discriminant analysis to create a linear projection of gene expression measurements that maximizes the separation of different sample classes. Relative to other typical classification methods, this method provides insights into the discriminating characteristics of expression measurements in terms of the contribution of individual genes to the definition of distinct physiological states. This projection method also facilitates visualization of classification results in a reduced dimensional space. Examples from four different cases demonstrate the ability of the method to produce well-separated groups in the projection space and to identify important genes for defining physiological states. The method can be augmented to also include data from the proteomic and metabolic phenotypes and can be useful in disease diagnosis, drug screening and bioprocessing applications.

AB - Motivation: The increasing use of DNA microarrays to probe cell physiology requires methods for visualizing different expression phenotypes and explicitly connecting individual genes to discriminating expression features. Such methods should be robust and maintain biological interpretability. Results: We propose a method for the mapping of the physiological state of cells and tissues from multidimensional expression data such as those obtained with DNA microarrays. The method uses Fisher discriminant analysis to create a linear projection of gene expression measurements that maximizes the separation of different sample classes. Relative to other typical classification methods, this method provides insights into the discriminating characteristics of expression measurements in terms of the contribution of individual genes to the definition of distinct physiological states. This projection method also facilitates visualization of classification results in a reduced dimensional space. Examples from four different cases demonstrate the ability of the method to produce well-separated groups in the projection space and to identify important genes for defining physiological states. The method can be augmented to also include data from the proteomic and metabolic phenotypes and can be useful in disease diagnosis, drug screening and bioprocessing applications.

UR - http://www.scopus.com/inward/record.url?scp=0036677672&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036677672&partnerID=8YFLogxK

U2 - 10.1093/bioinformatics/18.8.1054

DO - 10.1093/bioinformatics/18.8.1054

M3 - Article

C2 - 12176828

AN - SCOPUS:0036677672

VL - 18

SP - 1054

EP - 1063

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 8

ER -