Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
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 Verlagsversion bestellen
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/ .
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Sammelbandbeitrag/Buchkapitel
Schlagwörter Breast Cancer ; Classification ; De Novo Pathways ; Disease Subtyping
ISSN (print) / ISBN 1064-3745
Bandtitel Protein-Protein Interaction Networks
Zeitschrift Methods in Molecular Biology
Quellenangaben Band: 2074, Seiten: 201-213
Verlagsort Berlin [u.a.]
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)