Analysis of super-enhancer using machine learning and its application to medical biology.

ABSTRACT: The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this revi

SUBMITTER: Hamamoto R 

PROVIDER: S-EPMC10199775 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature