Article

Providing An Optimized Model to Detect Driver Genes From Heterogeneous Cancer Samples, Using Restriction in Subspace Learning

2020-11-23

Abstract excerpt

<title>Abstract</title> <p>Extracting the drivers from genes with mutation, and segregation of driver and passenger genes are known as the most controversial issues in cancer studies. According to the heterogeneity of cancer, it is not possible to identify indicators under a group of associated drivers, in order to identify a group of patients with diseases related to these subgroups. Therefore, the precise ident...

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Literature Corpus work: 4a06d72c-a01a-515d-b086-1481534cc423
DOI: 10.21203/rs.3.rs-112114/v1

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