MILVA: An interactive tool for the exploration of multidimensional microarray data

Davide D'Alimonte; David Lowe; Ian T Nabney; Vassilis Mersinias; Colin P Smith

doi:10.1093/bioinformatics/bti676

MILVA: An interactive tool for the exploration of multidimensional microarray data

Davide D'Alimonte, David Lowe, Ian T Nabney, Vassilis Mersinias, Colin P Smith

Research output: Contribution to journal › Article (Academic Journal) › peer-review

5 Citations (Scopus)

Abstract

Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

Original language	English
Pages (from-to)	4192-4193
Number of pages	2
Journal	Bioinformatics
Volume	21
Issue number	22
DOIs	https://doi.org/10.1093/bioinformatics/bti676
Publication status	Published - 2005

Keywords

cluster analysis, computational biology, computer graphics, statistical data interpretation, gene expression regulation, Internet, oligonucleotide array sequence analysis, automated pattern recognition, probability, programming languages, sensitivity and specificity, sequence alignment, DNA sequence analysis, software, user-computer interface

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@article{232d1440032640d9b653ff71209bb358,

title = "MILVA: An interactive tool for the exploration of multidimensional microarray data",

abstract = "Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.",

keywords = "cluster analysis, computational biology, computer graphics, statistical data interpretation, gene expression regulation, Internet, oligonucleotide array sequence analysis, automated pattern recognition, probability, programming languages, sensitivity and specificity, sequence alignment, DNA sequence analysis, software, user-computer interface",

author = "Davide D'Alimonte and David Lowe and Nabney, \{Ian T\} and Vassilis Mersinias and Smith, \{Colin P\}",

year = "2005",

doi = "10.1093/bioinformatics/bti676",

language = "English",

volume = "21",

pages = "4192--4193",

journal = "Bioinformatics",

issn = "1367-4811",

publisher = "Oxford University Press",

number = "22",

}

TY - JOUR

T1 - MILVA: An interactive tool for the exploration of multidimensional microarray data

AU - D'Alimonte, Davide

AU - Lowe, David

AU - Nabney, Ian T

AU - Mersinias, Vassilis

AU - Smith, Colin P

PY - 2005

Y1 - 2005

N2 - Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

AB - Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

KW - cluster analysis, computational biology, computer graphics, statistical data interpretation, gene expression regulation, Internet, oligonucleotide array sequence analysis, automated pattern recognition, probability, programming languages, sensitivity and

U2 - 10.1093/bioinformatics/bti676

DO - 10.1093/bioinformatics/bti676

M3 - Article (Academic Journal)

SN - 1367-4811

VL - 21

SP - 4192

EP - 4193

JO - Bioinformatics

JF - Bioinformatics

IS - 22

ER -

MILVA: An interactive tool for the exploration of multidimensional microarray data

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Keywords

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