Our publications related to cancer biomarkers

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Filters: Author is Lehmann-Che, Jacqueline [Clear All Filters]

2014

Győrffy B, Bottai G, Lehmann-Che J, Kéri G, Orfi L, Iwamoto T, Desmedt C, Bianchini G, Turner NC, de Thè H et al.. 2014. TP53 mutation-correlated genes predict the risk of tumor relapse and identify MPS1 as a potential therapeutic kinase in TP53-mutated breast cancers.. Mol Oncol. 8(3):508-19.

How to cite the RS calculator

RecurrenceOnline: an online analysis tool to determine breast cancer recurrence and hormone receptor status using microarray data, Breast Cancer Res Treat (2012). Read it here.

How to cite the dynamic re-training algorithm

Dynamic classification using case-specific training cohorts outperforms static gene expression signatures in breast cancer, Int J Cancer (2015). Read it here.

Techshow

On the Hungarian Innovation TechShow RecurrenceOnline has been selected as one of the 21 most innovative ideas shaping our future.

Semmelweis Journal

RecurrenceOnline has been described in the Semmelweis Journal. Read the pdf version here (only in Hungarian).

Projects

RecurrenceOnline was featured in Projects Magazine, Europe's leading science and technology research magazine. Download the pdf here.

Our publications related to cancer biomarkers

How to cite the RS calculator

How to cite the dynamic re-training algorithm

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Semmelweis Journal

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