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

页码：23 / 41

页数：19

共 50 条

[31] Perspective on the design of a knowledge-based system embedding Linked Data for process planning
Rehage, Gerald
Joppen, Robert
Gausemeier, Juergen
3RD INTERNATIONAL CONFERENCE ON SYSTEM-INTEGRATED INTELLIGENCE: NEW CHALLENGES FOR PRODUCT AND PRODUCTION ENGINEERING, 2016, 26 : 267 - 276
[32] A knowledge-based data model and query algebra for the next-generation web
Sheng, Qiu-Jian
Shi, Zhong-Zhi
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2004, 3007 : 489 - 499
[33] ProCAVIAR: Hybrid Data-Driven and Probabilistic Knowledge-Based Activity Recognition
Bettini, Claudio
Civitarese, Gabriele
Giancane, Davide
Presotto, Riccardo
IEEE ACCESS, 2020, 8 : 146876 - 146886
[34] Toward a Knowledge-Based Data Backbone for Seamless Digital Engineering in Smart Factories
Perzylo, Alexander
Kessler, Ingmar
Profanter, Stefan
Rickert, Markus
2020 25TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2020, : 164 - 171
[35] A knowledge-based data model and query algebra for the next-generation web
Sheng, QJ
Shi, ZZ
ADVANCED WEB TECHNOLOGIES AND APPLICATIONS, 2004, 3007 : 489 - 499
[36] Knowledge-based Fragment Binding Prediction
Tang, Grace W.
Altman, Russ B.
PLOS COMPUTATIONAL BIOLOGY, 2014, 10 (04)
[37] Knowledge-based recommendation with contrastive learning
He, Yang
Zheng, Xu
Xu, Rui
Tian, Ling
HIGH-CONFIDENCE COMPUTING, 2023, 3 (04):
[38] Knowledge-based modelling applied to synucleinopathies
Kamsu-Foguem, B.
Tiako, P. F.
Mutafungwa, E.
Foguem, C.
EUROPEAN GERIATRIC MEDICINE, 2015, 6 (04) : 381 - 388
[39] Biomedical knowledge discovery based on Sentence-BERT
Shen S.
Liu X.
Sun H.
Wang D.
Proceedings of the Association for Information Science and Technology, 2020, 57 (01)
[40] Knowledge-Based Dialogue System for the Ageing Support on Daily Activities
Vizcarra, Julio
Jokinen, Kristiina
HUMAN ASPECTS OF IT FOR THE AGED POPULATION: TECHNOLOGY IN EVERYDAY LIVING, PT II, 2022, 13331 : 122 - 133

← 1 2 3 4 5 →