Extracting and explaining biological knowledge in microarray data

Paul J. Kennedy; Simeon J. Simoff; David B. Skillicorn; Daniel R. Catchpoole; Honghua Dai; Ramakrishnan Srikant; Chengqi Zhang

Extracting and explaining biological knowledge in microarray data

Paul J. Kennedy, Simeon J. Simoff, David B. Skillicorn, Daniel R. Catchpoole, Honghua Dai, Ramakrishnan Srikant, Chengqi Zhang

School of Computer, Data & Mathematical Sciences

Research output: Chapter in Book / Conference Paper › Conference Paper

Abstract

High throughput technologies produce large biological datasets that may lead to greater understanding of the biological mechanisms behind diseases such as cancer. However, progress has been slow in extracting meaningful information from these datasets. We describe a method of clustering lists of genes mined from a microarray dataset using functional information from the Gene Ontology. The method uses relationships between terms in the ontology both to build clusters and to extract meaningful cluster descriptions. The approach is general and may be applied to assist explanation other datasets associated with ontologies.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining : Proceedings of the 8th Pacific-Asia Conference (PAKDD), held in Sydney, Australia, 26-28 May, 2004
Publisher	Springer
Number of pages	1
ISBN (Print)	354022064X
Publication status	Published - 2004
Event	Pacific-Asia Conference on Knowledge Discovery and Data Mining - Duration: 13 May 2013 → …

Conference

Conference	Pacific-Asia Conference on Knowledge Discovery and Data Mining
Period	13/05/13 → …

Keywords

cluster analysis
bioinformatics
DNA microarrays
decomposition methods
genes

Cite this

@inproceedings{f0d84d93ff994f3d97dbfdfc0f61442f,

title = "Extracting and explaining biological knowledge in microarray data",

abstract = "High throughput technologies produce large biological datasets that may lead to greater understanding of the biological mechanisms behind diseases such as cancer. However, progress has been slow in extracting meaningful information from these datasets. We describe a method of clustering lists of genes mined from a microarray dataset using functional information from the Gene Ontology. The method uses relationships between terms in the ontology both to build clusters and to extract meaningful cluster descriptions. The approach is general and may be applied to assist explanation other datasets associated with ontologies.",

keywords = "cluster analysis, bioinformatics, DNA microarrays, decomposition methods, genes",

author = "Kennedy, {Paul J.} and Simoff, {Simeon J.} and Skillicorn, {David B.} and Catchpoole, {Daniel R.} and Honghua Dai and Ramakrishnan Srikant and Chengqi Zhang",

year = "2004",

language = "English",

isbn = "354022064X",

booktitle = "Advances in Knowledge Discovery and Data Mining : Proceedings of the 8th Pacific-Asia Conference (PAKDD), held in Sydney, Australia, 26-28 May, 2004",

publisher = "Springer",

note = "Pacific-Asia Conference on Knowledge Discovery and Data Mining ; Conference date: 13-05-2013",

}

Kennedy, PJ, Simoff, SJ, Skillicorn, DB, Catchpoole, DR, Dai, H, Srikant, R & Zhang, C 2004, Extracting and explaining biological knowledge in microarray data. in Advances in Knowledge Discovery and Data Mining : Proceedings of the 8th Pacific-Asia Conference (PAKDD), held in Sydney, Australia, 26-28 May, 2004. Springer, Pacific-Asia Conference on Knowledge Discovery and Data Mining, 13/05/13.

Extracting and explaining biological knowledge in microarray data. / Kennedy, Paul J.; Simoff, Simeon J.; Skillicorn, David B. et al.
Advances in Knowledge Discovery and Data Mining : Proceedings of the 8th Pacific-Asia Conference (PAKDD), held in Sydney, Australia, 26-28 May, 2004. Springer, 2004.

Research output: Chapter in Book / Conference Paper › Conference Paper

TY - GEN

T1 - Extracting and explaining biological knowledge in microarray data

AU - Kennedy, Paul J.

AU - Simoff, Simeon J.

AU - Skillicorn, David B.

AU - Catchpoole, Daniel R.

AU - Dai, Honghua

AU - Srikant, Ramakrishnan

AU - Zhang, Chengqi

PY - 2004

Y1 - 2004

N2 - High throughput technologies produce large biological datasets that may lead to greater understanding of the biological mechanisms behind diseases such as cancer. However, progress has been slow in extracting meaningful information from these datasets. We describe a method of clustering lists of genes mined from a microarray dataset using functional information from the Gene Ontology. The method uses relationships between terms in the ontology both to build clusters and to extract meaningful cluster descriptions. The approach is general and may be applied to assist explanation other datasets associated with ontologies.

AB - High throughput technologies produce large biological datasets that may lead to greater understanding of the biological mechanisms behind diseases such as cancer. However, progress has been slow in extracting meaningful information from these datasets. We describe a method of clustering lists of genes mined from a microarray dataset using functional information from the Gene Ontology. The method uses relationships between terms in the ontology both to build clusters and to extract meaningful cluster descriptions. The approach is general and may be applied to assist explanation other datasets associated with ontologies.

KW - cluster analysis

KW - bioinformatics

KW - DNA microarrays

KW - decomposition methods

KW - genes

UR - http://handle.uws.edu.au:8081/1959.7/45298

M3 - Conference Paper

SN - 354022064X

BT - Advances in Knowledge Discovery and Data Mining : Proceedings of the 8th Pacific-Asia Conference (PAKDD), held in Sydney, Australia, 26-28 May, 2004

PB - Springer

T2 - Pacific-Asia Conference on Knowledge Discovery and Data Mining

Y2 - 13 May 2013

ER -

Extracting and explaining biological knowledge in microarray data

Abstract

Conference

Keywords

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