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Interoperable Data for KnetMiner and DFW Use Cases
1. Interoperable Data for KnetMiner and
DFW Use Cases
Elixir BioHackathon 2021
Marco Brandizi <marco.brandizi@rothamsted.ac.uk>
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background source: https://alimentaciosostenible.barcelona/en/protecting-planet/urban-agriculture
2. Typical KnetMiner Searches
Based on publications, which genes are related to the yellow rust disease?
In which biological processes are their encoded proteins involved?
4. schema.org, Bioschemas, AgriSchemas
• Ideal for:
• Heterogeneous data, sources, formats
• Informal data
• Exploratory research (including AI)
• Integration/sharing advantages
• Simple and informal, but it’s easy to integrate
• other data (eg, OBO ontologies)
• FAIR-oriented support (eg, Google Dataset
Search)
• The AgriSchemas Project
• A set of use cases modelled with
schema.org, bioschemas
• Reusable data ETL tools
• bioschemas additions and extensions
8. AgriSchemas: Gene Expression (and EBI/GXA Data)
Based on publications, which genes are related to the yellow rust disease?
In which biological processes are their encoded proteins involved?
In which tissues are the genes expressed?
11. AgriSchemas: Ontologies and Ontology Annotations
Live: http://knetminer.org/data/rdf/resources/cond_outer_pericarp
12. AgriSchemas: Gene Expression (and EBI/GXA Data)
Based on publications, which genes are related to the yellow rust disease?
In which biological processes are their encoded proteins involved?
In which tissues are the genes expressed?
What is the experimental evidence (ie, Field Trials) for the gene ex?
13. AgriSchemas: Studies/Experiments/Field Trials
Live: http://knetminer.org/data/rdf/resources/exp_E-MTAB-3103
Detailed modelling about Field Trials:
https://github.com/Rothamsted/agri-schemas/tree/master/doc/miappe-use-case
Use case (includes study, samples, assays):
https://github.com/Rothamsted/agri-schemas/blob/master/doc/miappe-use-case.ttl
14. Ongoing Work
Use case Data Types Data Sources Status
Molecular Biology Gene, Protein, Pathway
encodes, participates
Via Knetminer: ENSEMBL, UniProt,
TILLING, wheat-expression.com, KEGG
Done.
Ontology Annotations Ontology Term (schema:DefinedTerm)
dc:type, schema:additionalType
Via Knetminer: GO, PO, CROP-Onto Done.
Experiments Study, agri:StudyFactor, PropertyValue EBI/GXA, GLTen, MIAPPE/BrAPI
sources, ?
GXA Done
GLTen use case drafted
MIAPPE, use case drafted
Literature agri:ScholarlyPublication
mentions
Via Knetminer: PubMed Done
Gene Expression bioschema:expressedIn, reified
statements, agri:evidence, agri:pvalue,
agri:baseCondition
EBI/GXA, Via Knetminer: wheat-
expression.com
GXA
Host-pathogen interaction Gene, Phenotype,
agri:ScholarlyPublication
agri:HostPathogenInteraction
agri:evidence
PHI-Base Use case drafted
Weather ? ? TO DO
Dataset metadata Dataset, DataCatalog
license, distribution
knetminer.org/data ongoing
15. References
• AgriSchemas
• https://github.com/Rothamsted/agri-schemas
• Use cases: https://github.com/Rothamsted/agri-schemas/tree/master/drafts/201904-dfw-
hackathon
• Real data & ETL tools: https://github.com/Rothamsted/agri-schemas/tree/master/dfw-dataset
• Knetminer
• Web site: http://knetminer.org
• Publication: https://doi.org/10.1111/pbi.13583
• Case study about FAIR data:
• https://knetminer.com/cases/the-power-of-standardised-and-fair-knowledge-graphs.html
• FAIR data infrastructure: https://doi.org/10.1515/jib-2018-0023
• Data endpoint: http://knetminer.org/data
• DFW
• AgriSchemas and DFW:
• https://designingfuturewheat.org.uk/dfw-and-fair-agriculture-data-the-knetminer-
experience/
• Me
• https://www.slideshare.net/mbrandizi, https://marcobrandizi.info/about-me/