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Prediction and uncertainty in the analysis of gene expression profiles

Spang, Rainer, Zuzan, H., West, M., Nevins, J., Blanchette, C. and Marks, J. R. (2002) Prediction and uncertainty in the analysis of gene expression profiles. In Silico Biology 2 (3), pp. 369-381.

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Other URL: http://content.iospress.com/articles/in-silico-biology/isb00056


Abstract

We have developed a complete statistical model for the analysis of tumor specific gene expression profiles. The approach provides investigators with a global overview on large scale gene expression data, indicating aspects of the data that relate to tumor phenotype, but also summarizing the uncertainties inherent in classification of tumor types. We demonstrate the use of this method in the ...

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Item type:Article
Date:2002
Institutions:Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang)
Identification Number:
ValueType
12542420PubMed ID
Keywords:Computational diagnostics, gene expression analysis, expression profiles, micro array, gene chip, breast cancer, estrogen receptor status, Bayesian statistics, Bayesian regularization, binary regression, probit model, G-prior, singular value decomposition, predictive diagnosis, prognosis, tumor classification, uncertainty, factor regression, ridge regression, machine learning
Dewey Decimal Classification:600 Technology > 610 Medical sciences Medicine
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:No
Item ID:34403
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