OpenSSL SSL_connect: Connection reset by peer in connection to v2.sherpa.ac.uk:443 PuSH - Publication Server of Helmholtz Zentrum München: De novo pathway-based classification of breast cancer subtypes.

PuSH - Publication Server of Helmholtz Zentrum München

List, M.* ; Alcaraz, N.* ; Batra, R.

De novo pathway-based classification of breast cancer subtypes.

In: Protein-Protein Interaction Networks. Berlin [u.a.]: Springer, 2019. 201-213 (Methods Mol. Biol. ; 2074)
DOI PMC
Open Access Green as soon as Postprint is submitted to ZB.
Breast cancer is a heterogeneous disease for which various clinically relevant subtypes have been reported. These subtypes are characterized by molecular differences which direct treatment selection. The state of the art for breast cancer subtyping utilizes histochemistry or gene expression to measure a few selected markers. However, classification based on molecular pathways (rather than individual markers) is a more robust way to classify breast cancer samples into known subtypes.Here, we present PathClass, a web application that allows its users to predict breast cancer subtypes using various traditional as well as advanced methods. This includes methods based on classical gene expression panels as well as de novo pathway-based predictors. Users can predict labels for datasets in the Gene Expression Omnibus or upload their own expression profiling data.Availability: https://pathclass.compbio.sdu.dk/ .
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Publication type Article: Edited volume or book chapter
Corresponding Author
Keywords Breast Cancer ; Classification ; De Novo Pathways ; Disease Subtyping
ISSN (print) / ISBN 1064-3745
e-ISSN 1940-6029
Book Volume Title Protein-Protein Interaction Networks
Journal Methods in Molecular Biology
Quellenangaben Volume: 2074, Issue: , Pages: 201-213 Article Number: , Supplement: ,
Publisher Springer
Publishing Place Berlin [u.a.]
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)