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High-Dimensional Profiling for Computational Diagnosis

Lottaz, Claudio, Gronwald, Wolfram , Spang, Rainer and Engelmann, Julia C. (2017) High-Dimensional Profiling for Computational Diagnosis. In: Bioinformatics : Volume II: Structure, Function, and Applications. Methods in Molecular Biology, 1526. Springer, New York, pp. 205-229. ISBN 978-1-4939-6611-0.

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Other URL: http://link.springer.com/protocol/10.1007%2F978-1-4939-6613-4_12, http://www.springerprotocols.com/BookToc/doi/10.1007/978-1-4939-6613-4?uri=/Abstract/doi/10.1007/978-1-4939-6613-4_12


Abstract

New technologies allow for high-dimensional profiling of patients. For instance, genome-wide gene expression analysis in tumors or in blood is feasible with microarrays, if all transcripts are known, or even without this restriction using high-throughput RNA sequencing. Other technologies like NMR finger printing allow for high-dimensional profiling of metabolites in blood or urine. Such ...

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Item type:Book section
Date:2017
Institutions:Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang)
Identification Number:
ValueType
27896744PubMed ID
10.1007/978-1-4939-6613-4_12DOI
Keywords:Feature selection; Gene expression profiles; Metabolite analysis; Microarrays; Model assessment; NMR finger printing; RNA sequencing; Statistical classification; Supervised 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:Yes
Item ID:34975
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