Knowledge-Based Biomedical Data Science

被引:27
|
作者
Callahan, Tiffany J. [1 ,2 ]
Tripodi, Ignacio J. [3 ]
Pielke-Lombardo, Harrison [1 ,2 ]
Hunter, Lawrence E. [1 ,2 ]
机构
[1] Univ Colorado Denver Anschutz Med Campus, Computat Biosci Program, Aurora, CO 80045 USA
[2] Univ Colorado Denver Anschutz Med Campus, Dept Pharmacol, Aurora, CO 80045 USA
[3] Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA
来源
ANNUAL REVIEW OF BIOMEDICAL DATA SCIENCE, VOL 3, 2020 | 2020年 / 3卷
关键词
knowledge graph; ontology; natural language processing; knowledge discovery; SemanticWeb; knowledge graph embeddings; DRUG DISCOVERY; SCALE; GRAPH;
D O I
10.1146/annurev-biodatasci-010820-091627
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Knowledge-based biomedical data science involves the design and implementation of computer systems that act as if they knew about biomedicine. Such systems depend on formally represented knowledge in computer systems, often in the form of knowledge graphs. Here we survey recent progress in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as progress on approaches for creating knowledge graphs. Major themes include the relationships between knowledge graphs and machine learning, the use of natural language processing to construct knowledge graphs, and the expansion of novel knowledge-based approaches to clinical and biological domains.
引用
收藏
页码:23 / 41
页数:19
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