This paper proposes an innovative data structure to be used as a backbone in designing microarray phenotype sample classifiers. The data structure is based on graphs and it is built from a differential analysis of the expression levels of healthy and diseased tissue samples in a microarray dataset. The proposed data structure is built in such a way that, by construction, it shows a number of properties that are perfectly suited to address several problems like feature extraction, clustering, and classification.
Differential gene expression graphs: A data structure for classification in DNA microarrays / Benso, Alfredo; DI CARLO, Stefano; Politano, GIANFRANCO MICHELE MARIA; Sterpone, Luca. - STAMPA. - (2008), pp. 1-6. (Intervento presentato al convegno IEEE 8th International Conference on BioInformatics and BioEngineering (BIBE) tenutosi a Athens, GR nel 8-10 Ott. 2008) [10.1109/BIBE.2008.4696689].
Differential gene expression graphs: A data structure for classification in DNA microarrays
BENSO, Alfredo;DI CARLO, STEFANO;POLITANO, GIANFRANCO MICHELE MARIA;STERPONE, Luca
2008
Abstract
This paper proposes an innovative data structure to be used as a backbone in designing microarray phenotype sample classifiers. The data structure is based on graphs and it is built from a differential analysis of the expression levels of healthy and diseased tissue samples in a microarray dataset. The proposed data structure is built in such a way that, by construction, it shows a number of properties that are perfectly suited to address several problems like feature extraction, clustering, and classification.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/1894256
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