=Paper=
{{Paper
|id=Vol-1795/paper40
|storemode=property
|title=Answering Scientific Questions with linked European Nanosafety Data
|pdfUrl=https://ceur-ws.org/Vol-1795/paper40.pdf
|volume=Vol-1795
|authors=Egon Willighagen,Micha Rautenberg,Denis Gebele,Linda Rieswijk,Friederike Ehrhart,Jiakang Chang,Georgios Drakakis,Penny Nymark,Pekka Kohonen,Gareth Owen,Haralambos Sarimveis,Christoph Helma,Nina Jeliazkova
|dblpUrl=https://dblp.org/rec/conf/swat4ls/WillighagenRGRE16
}}
==Answering Scientific Questions with linked European Nanosafety Data==
https://ceur-ws.org/Vol-1795/paper40.pdf
Answering scientific questions with linked
European nanosafety data
Egon Willighagen1 , Micha Rautenberg2 , Denis Gebele2 , Linda Rieswijk1 ,
Friederike Ehrhart1 , Jiakang Chang3 , Georgios Drakakis4 , Penny Nymark5 ,
Pekka Kohonen5 , Gareth Owen3 , Haralambos Sarimveis4 , Christoph Helma2 ,
and Nina Jeliazkova6
1
Maastricht University, Maastricht, NL
2
in silico toxicology gmbh, Freiburg, DE
3
EMBL-EBI, Hinxton, UK
4
National Technical University of Athens, Athens, GR
5
Misvik Biology, Turku, FI
6
IdeaConsult Ltd., Sofia, BG
Nanomaterials are increasingly used in healthcare and consumer products.
The European community seeks solutions to assess the safety of these materials
with experimental research data. Ideally, read across and predictive toxicology
approaches can then be used to answer questions if a class of metal oxides is
genotoxic or not. If successful, this will replace animal testing in bringing new
nanomaterials to the market.
The eNanoMapper project (http://enanomapper.net/) is an FP7 project de-
veloping an ontology and database solutions for the data generated in the EU
NanoSafety Cluster [2, 3]. This includes extracts of experimental data from,
for example, cell line experiments, environmental toxicity studies, and high-
throughput screening results. More important, however, is that this data is no
longer static but can be queried and analysed. That is, to make the best use of
this data, integration with other life science databases is needed, such as protein
sequence database like Uniprot and compound databases such as ChEMBL [7],
UniProt [5] and PubChem [1]. Doing so allows us to test scientific hypotheses
such as about the genotoxicity of metal oxides, whether chemically similar nano-
materials have similar bioactivities, or whether protein coronas contain prefer-
ably proteins involved in specific biological processes.
Semantic Web standards are an increasingly central interoperability layer
linking experimental data to scientific knowledge. eNanoMapper has been work-
ing on extending the semantics of the database software to import and export
data in a serialization based on the Resource Description Framework (RDF) and
the eNanoMapper ontology. The RDF data is made available as dereferenceable
data and via a SPARQL endpoint (https://sparql.enanomapper.net/) and with
a graphical query interface (https://query.enanomapper.net/). These technolo-
gies are then used to support the research data management in the community.
First, data completeness [4] is checked by using SPARQL queries, thereby high-
lighting missing data, and allowing support of pattern recognition [6]. Second,
the scientific questions predefined by the eNanoMapper project, such as men-
tioned earlier in this abstract, are supported by SPARQL queries aggregating
the relevant data. Finally, the eNanoMapper RDF is enriched with links to other
Linked Open Data Cloud resources (e.g. ChEMBL, PubChem) to support fur-
ther nanosafety research.
Source code for various components of this work are available from GitHub
at https://github.com/enanomapper/.
References
1. Fu, G., Batchelor, C., Dumontier, M., Hastings, J., Willighagen, E., Bolton, E.: Pub-
ChemRDF: towards the semantic annotation of PubChem compound and substance
databases. Journal of Cheminformatics 7(1), 34+ (Jul 2015)
2. Hastings, J., Jeliazkova, N., Owen, G., Tsiliki, G., Munteanu, C.R., Steinbeck, C.,
Willighagen, E.: eNanoMapper: harnessing ontologies to enable data integration
for nanomaterial risk assessment. Journal of Biomedical Semantics 6(1), 10+ (Mar
2015)
3. Jeliazkova, N., Chomenidis, C., Doganis, P., Fadeel, B., Grafström, R., Hardy, B.,
Hastings, J., Hegi, M., Jeliazkov, V., Kochev, N., Kohonen, P., Munteanu, C.R.,
Sarimveis, H., Smeets, B., Sopasakis, P., Tsiliki, G., Vorgrimmler, D., Willigha-
gen, E.: The eNanoMapper database for nanomaterial safety information. Beilstein
Journal of Nanotechnology 6, 1609–1634 (Jul 2015)
4. Marchese Robinson, R.L., Lynch, I., Peijnenburg, W., Rumble, J., Klaessig, F., Mar-
quardt, C., Rauscher, H., Puzyn, T., Purian, R., Åberg, C., Karcher, S., Vriens, H.,
Hoet, P., Hoover, M.D., Hendren, C.O., Harper, S.L.: How should the completeness
and quality of curated nanomaterial data be evaluated? Nanoscale 8(19), 9919–9943
(2016)
5. The UniProt Consortium: Activities at the universal protein resource (UniProt).
Nucleic Acids Research 42(D1), D191–D198 (Jan 2014)
6. Willighagen, E., Alvarsson, J., Andersson, A., Eklund, M., Lampa, S., Lapins, M.,
Spjuth, O., Wikberg, J.: Linking the resource description framework to cheminfor-
matics and proteochemometrics. Journal of Biomedical Semantics 2(Suppl 1), S6+
(2011)
7. Willighagen, E.L., Waagmeester, A., Spjuth, O., Ansell, P., Williams, A.J.,
Tkachenko, V., Hastings, J., Chen, B., Wild, D.J.: The ChEMBL database as linked
open data. Journal of Cheminformatics 5(1), 23+ (May 2013)