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Evaluation of single-sample network inference methods for precision oncology - npj Systems Biology and Applications

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Evaluation of single-sample network inference methods for precision oncology - npj Systems Biology and Applications

A major challenge in precision oncology is to detect targetable cancer vulnerabilities in individual patients. Modeling high-throughput omics data in biological networks allows identifying key molecules and processes of tumorigenesis. Traditionally, network inference methods rely on many samples to contain sufficient information for learning, resulting in aggregate networks.

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Evaluation of single-sample network inference methods for precision oncology - npj Systems Biology and Applications

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Evaluation of single-sample network inference methods for precision oncology - npj Systems Biology and Applications

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