Article

PAN: Personalized Annotation-based Networks for the Prediction of Breast Cancer Relapse

2019-01-29

Abstract excerpt

The classification of clinical samples based on gene expression data is an important part of precision medicine. However, it has proved difficult to accurately predict survival outcomes and treatment responses for cancer patients. In this manuscript, we show how transforming gene expression data into a set of personalized (sample-specific) networks can allow us to harness existing graph-based methods to improve cl...

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Literature Corpus work: c3d3ffea-5194-5a5d-838d-5d14cc6f31ec
DOI: 10.1101/534628

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