A Review of Deep Genomics Applying Machine Learning in Genomic Medicine.
- Author:
Tae Hyung KIM
1
Author Information
- Publication Type:Review
- Keywords: deep learning; machine learning; genomic data; genome biology; genome medicine
- MeSH: Biology; Dataset; DNA; Gene Expression; Genomics*; Learning; Machine Learning*; Phenotype; Protein Binding; RNA, Messenger
- From:Hanyang Medical Reviews 2017;37(2):93-98
- CountryRepublic of Korea
- Language:Korean
- Abstract: Genomic medicine is to determine how an individual's DNA alteration can affect the risk of various diseases and to understand mechanisms and design targeted treatments. Here, we focus on how machine learning helps model the relationship between DNA and molecular phenotypes in a cell. Modern biology enables high throughput measurements of many cellular variables that can be handled as a training target for predictable models, such as gene expression, splicing, and protein binding to DNA or mRNA. With the increasing availability of large datasets and advanced computer skills such as deep learning, researchers have opened a new era in effective genomic medicine.
