SAPP
Please note that SAPP-2.0 is nearly finished and we are working on upgrading the documentation
Semantic Annotation Platform with Provenance
SAPP is a Semantic genome Annotation Platform with Provenance and is designed on the basis of Semantic Web. The platform and corresponding modules allows you to annotate genomes of various qualities linked to a full chain of data provenance. Resulting is an annotated genome in the RDF data model which you can query and analyse using SPARQL. Various modules are available which allows you to compare, annotate and visualise genomes and export your annotations to various standard genome annotation formats.
For a global overview of the modules available look under the Modules section on the left. The modules are broken up into three subsections. The Conversion section, allowing to convert various formats to the RDF data model. Genetic elements contains modules for the prediction of genes, tRNA, tmRNA and rRNAs with each containing a corresponding RDF model. Protein annotation contains modules to further annotate the proteins either predicted using the gene prediction module or through the conversion modules.
About us
SAPP is an initiative by the Laboratory of Systems and Synthetic Biology from Wageningen University & Research.
Funding
This work has received funding from the Research Council of Norway, No. 248792 (DigiSal) and from the European Union FP7 and H2020 under grant agreements No. 305340 (INFECT), No. 635536 (EmPowerPutida) and No. 634940 (MycoSynVac).
Contact
You can contact us at j...@wur.nl. SAPP is part of the Semantics Systems Biology initiative.
- Please submit bug reports and feature suggestions, here...
When using SAPP please cite
SAPP: functional genome annotation and analysis through a semantic framework using FAIR principles
Koehorst, Jasper J. and van Dam, Jesse C.J. and Saccenti, Edoardo and Martins dos Santos, Vitor A.P. and Suarez-Diez, Maria and Schaap, Peter J.
When referring to the SAPP ontology please cite
Interoperable genome annotation with GBOL, an extendable infrastructure for functional data mining
Jesse C.J. van Dam, Jasper Jan J. Koehorst, Jon Olav Vik, Peter J. Schaap, Maria Suarez-Diez
bioRxiv 184747; doi: https://doi.org/10.1101/184747