Chebifier: automating semantic classification in ChEBI to accelerate data-driven discovery-Reference-Cited by-同舟云学术

Chebifier: automating semantic classification in ChEBI to accelerate data-driven discovery

Published:2024 Issue:5 Volume:3 Page:896-907
ISSN:2635-098X
Container-title:Digital Discovery
language:en
Short-container-title:Digital Discovery

Author:

Glauer Martin¹,Neuhaus Fabian¹,Flügel Simon¹^ORCID,Wosny Marie²³,Mossakowski Till¹,Memariani Adel¹,Schwerdt Johannes¹⁴,Hastings Janna²³⁵^ORCID

Affiliation:

1. Otto von Guericke University, Magdeburg, Germany

2. Institute for Implementation Science in Health Care, University of Zurich, Switzerland

3. School of Medicine, University of St. Gallen, Switzerland

4. University of Applied Sciences Merseburg, Germany

5. Swiss Institute of Bioinformatics, Switzerland

Abstract

Connecting chemical structural representations with meaningful categories and semantic annotations representing existing knowledge enables data-driven digital discovery from chemistry data.

Funder

Deutsche Forschungsgemeinschaft

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/DD/D3DD00238A

Reference39 articles.

1. AI in drug discovery and its clinical relevance

2. Bioinformatics driven discovery of small molecule compounds that modulate the FOXM1 and PPARA pathway activities in breast cancer

3. Enhancing untargeted metabolomics using metadata-based source annotation

4. J.Hastings , The Gene Ontology Handbook , Springer New York , New York, NY , 2017 , vol. 1446 , pp. 3–13

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Fuzzy Loss for Ontology Classification;Lecture Notes in Computer Science;2024