Structured reviews for data and knowledge-driven research.
Animals
Biomedical Research
/ methods
Computational Biology
/ methods
Congenital Disorders of Glycosylation
/ genetics
Data Curation
/ methods
Data Mining
/ methods
Databases, Factual
Humans
Internet
Knowledge Bases
Peptide-N4-(N-acetyl-beta-glucosaminyl) Asparagine Amidase
/ deficiency
Systematic Reviews as Topic
Journal
Database : the journal of biological databases and curation
ISSN: 1758-0463
Titre abrégé: Database (Oxford)
Pays: England
ID NLM: 101517697
Informations de publication
Date de publication:
01 01 2020
01 01 2020
Historique:
received:
12
08
2019
revised:
21
01
2020
accepted:
07
02
2020
entrez:
14
4
2020
pubmed:
14
4
2020
medline:
2
2
2021
Statut:
ppublish
Résumé
Hypothesis generation is a critical step in research and a cornerstone in the rare disease field. Research is most efficient when those hypotheses are based on the entirety of knowledge known to date. Systematic review articles are commonly used in biomedicine to summarize existing knowledge and contextualize experimental data. But the information contained within review articles is typically only expressed as free-text, which is difficult to use computationally. Researchers struggle to navigate, collect and remix prior knowledge as it is scattered in several silos without seamless integration and access. This lack of a structured information framework hinders research by both experimental and computational scientists. To better organize knowledge and data, we built a structured review article that is specifically focused on NGLY1 Deficiency, an ultra-rare genetic disease first reported in 2012. We represented this structured review as a knowledge graph and then stored this knowledge graph in a Neo4j database to simplify dissemination, querying and visualization of the network. Relative to free-text, this structured review better promotes the principles of findability, accessibility, interoperability and reusability (FAIR). In collaboration with domain experts in NGLY1 Deficiency, we demonstrate how this resource can improve the efficiency and comprehensiveness of hypothesis generation. We also developed a read-write interface that allows domain experts to contribute FAIR structured knowledge to this community resource. In contrast to traditional free-text review articles, this structured review exists as a living knowledge graph that is curated by humans and accessible to computational analyses. Finally, we have generalized this workflow into modular and repurposable components that can be applied to other domain areas. This NGLY1 Deficiency-focused network is publicly available at http://ngly1graph.org/. Database URL: http://ngly1graph.org/. Network data files are at: https://github.com/SuLab/ngly1-graph and source code at: https://github.com/SuLab/bioknowledge-reviewer. asu@scripps.edu.
Identifiants
pubmed: 32283553
pii: 5818923
doi: 10.1093/database/baaa015
pmc: PMC7153956
pii:
doi:
Substances chimiques
Peptide-N4-(N-acetyl-beta-glucosaminyl) Asparagine Amidase
EC 3.5.1.52
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM089820
Pays : United States
Organisme : NCATS NIH HHS
ID : OT3 TR002019
Pays : United States
Informations de copyright
© The Author(s) 2020. Published by Oxford University Press.
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