期刊
CURRENT OPINION IN BIOTECHNOLOGY
卷 63, 期 -, 页码 126-134出版社
CURRENT BIOLOGY LTD
DOI: 10.1016/j.copbio.2019.12.021
关键词
-
资金
- National Human Genome Research Institute [R01 HG010067]
- Gordon and Betty Moore Foundation [GBMF 4552]
- National Cancer Institute [R01 CA237170]
- Alex's Lemonade Stand Foundation (CCDL)
In biomedical applications of machine learning, relevant information often has a rich structure that is not easily encoded as real-valued predictors. Examples of such data include DNA or RNA sequences, gene sets or pathways, gene interaction or coexpression networks, ontologies, and phylogenetic trees. We highlight recent examples of machine learning models that use structure to constrain model architecture or incorporate structured data into model training. For machine learning in biomedicine, where sample size is limited and model interpretability is crucial, incorporating prior knowledge in the form of structured data can be particularly useful. The area of research would benefit from performant open source implementations and independent benchmarking efforts.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据