Ontology-based prediction of cancer driver genes

Abstract excerpt

Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity, many driver mutations within a gene occur at low frequencies, which make it chall...

Topics

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• Computational Biology
• Exome
• Gene Ontology
• High-Throughput Nucleotide Sequencing
• Machine Learning
• Molecular Sequence Annotation
• Oncogenes
• ROC Curve

Identifiers and source

Literature Corpus work

d796ed76-db43-51fc-9cac-d3cde6759edd

DOI

10.1101/561480