Genesis: cluster analysis of microarray data

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ID: 291447
2002
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Abstract
Abstract Summary: 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. Availability: http://genome.tugraz.at Contact: zlatko.trajanoski@tugraz.at * To whom correspondence should be addressed.
Reference Key
openalex_W2170984819 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alexander Sturn, John Quackenbush, Zlatko Trajanoski
Journal BMC Bioinformatics
Year 2002
DOI
10.1093/bioinformatics/18.1.207
URL
https://academic.oup.com/bioinformatics/article-pdf/18/1/207/48850312/bioinformatics_18_1_207.pdf
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