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Gullermo Gonzalez

As seen in: BioRxiv
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Articles

CGPA: multi-context insights from the cancer gene prognosis atlas

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By Biwei Cao, Xiaoqing Yu, Gullermo Gonzalez, Amith R. Murthy
| BioRxiv
Abstract Cancer transcriptomic data are used extensively to interrogate the prognostic value of targeted genes, yet basic scientists and clinicians have predominantly relied on univariable survival analysis for this purpose. This method often fails to capture the full prognostic potential and contextual relevance of the genes under study, inadvertently omitting a group of genes we term univariable missed-opportunity prognostic (UMOP) genes.
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