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PMID: 11836235 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

Genesis: cluster analysis of microarray data.

Bioinformatics (Oxford, England) ·Vol. 18 ·No. 1 ·2002-01-00 ·Pages 207-8

Sturn A, Quackenbush J, Trajanoski Z

Abstract

A versatile, platform independent and easy to use Java suite for large-scale gene expression analysis was developed. Genesis integrates various tools for microarray data analysis such as filters, normalization and visualization tools, distance measures as well as common clustering algorithms including hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The results of the clustering are transparent across all implemented methods and enable the analysis of the outcome of different algorithms and parameters. Additionally, mapping of gene expression data onto chromosomal sequences was implemented to enhance promoter analysis and investigation of transcriptional control mechanisms.

MeSH Terms
Algorithms Cluster Analysis Computational Biology Gene Expression Profiling/statistics & numerical data Oligonucleotide Array Sequence Analysis/statistics & numerical data Principal Component Analysis Programming Languages Promoter Regions, Genetic Software Transcription, Genetic
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Sturn Alexander
Institute of Biomedical Engineering, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.
Quackenbush John
Trajanoski Zlatko
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2002-01-00
Pages
207-8
Language
English
Region
England
NLM ID
9808944
Subset
IM
Analysis Services
Analysis Services

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