Computational Prediction of Probable Single Nucleotide Polymorphism-Cancer Relationships.

ABSTRACT: Genetic variations such as single nucleotide polymorphisms (SNPs) can cause susceptibility to cancer. Although thousands of genetic variants have been identified to be associated with different cancers, the molecular mechanisms of cancer remain unknown. There is not a particular dataset of relationships between cancer and SNPs, as a bipartite network, for computational analysis and prediction. Link prediction as a computational graph analysis method can help us to gain new insight into the network. In this article, after creating a network between cancer and SNPs using SNPedia and Cancer Research UK databases, we evaluated the computational link prediction methods to foresee new SNP-Cancer relationships. Results show that among the popular scoring methods based on network topology, for rel

SUBMITTER: Bakhtiari S 

PROVIDER: S-EPMC7364831 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature