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Erschienen in: Soft Computing 8/2011

01.08.2011 | Focus

Automatic summarisation and annotation of microarray data

verfasst von: Pietro H. Guzzi, Maria Teresa Di Martino, Giuseppe Tradigo, Pierangelo Veltri, Pierfrancesco Tassone, Pierosandro Tagliaferri, Mario Cannataro

Erschienen in: Soft Computing | Ausgabe 8/2011

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Abstract

The study of biological processes within cells is based on the measurement of the activity of different molecules, in particular genes and proteins whose activities are strictly related. The activity of genes is measured through a systematic investigation carried out by microarrays. Such technology enables the investigation of all the genes of an organism in a single experiment, encoding meaningful biological information. Nevertheless, the preprocessing of raw microarray data needs automatic tools that standardise such phase in order to: (a) avoiding errors in analysis phases, and (b) making comparable the results of different laboratories. The preprocessing problem is as much relevant as considering results obtained from analysis platforms of different vendors. Nevertheless, there is currently a lack of tools that allow to manage and preprocess multivendor dataset. This paper presents a software platform (called GSAT, General-purpose Summarisation and Annotation Tool) able to manage and preprocess microarray data. The GSAT allows the summarisation, normalisation and annotation of multivendor microarray data, using web services technology. First experiments and results on Affymetrix data samples are also discussed. GSAT is available online at http://​bioingegneria.​unicz.​it/​m-cs as a standalone application or as a plugin of the TMEV microarray data analysis platform.

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Metadaten
Titel
Automatic summarisation and annotation of microarray data
verfasst von
Pietro H. Guzzi
Maria Teresa Di Martino
Giuseppe Tradigo
Pierangelo Veltri
Pierfrancesco Tassone
Pierosandro Tagliaferri
Mario Cannataro
Publikationsdatum
01.08.2011
Verlag
Springer-Verlag
Erschienen in
Soft Computing / Ausgabe 8/2011
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-010-0600-4

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