<p>This is a poster delivered at the 16th International Workshop on Quantitative Structure Activity Relationships in Environmental and Health Sciences (QSAR2014), 16-20th June 2014, Milan, Italy: <a href="http://qsar2014.insilico.eu/">http://qsar2014.insilico.eu/</a></p>
<p>Disclaimers:</p>
<p>(1) this presentation has not undergone peer review</p>
<p>(2) this presentation may report preliminary results which may have been revised in subsequent publications</p>
<p>(3) no endorsement by third parties should be inferred</p>
<p>Presentation abstract:</p><p>
There are an
increasing number of (Q)SAR models to predict the toxicity and properties of nanomaterials
[1]. Indeed, in light of perceived uncertainties regarding their potential
health and environmental effects, as well as the drive towards reduced use of
animals for toxicity testing, the European Commission has funded a number of
projects looking at computational prediction of nanomaterial toxicity. The
NanoPUZZLES (www.nanopuzzles.eu) and NanoBRIDGES (www.nanobridges.eu) projects are
two such activities charged with developing grouping, read-across and (Q)SAR
approaches for modelling of nanomaterial toxicity. These approaches require adequate
quantities of high quality toxicological and physicochemical data on
well-characterised nanomaterials, which are being collected in both projects.
These data need to be available within an electronic database in a consistent
and interoperable manner to best support modelling. The NanoPUZZLES project is organising
collected data in a suitable electronic format that will be made available to
modellers via a publicly accessible database in accordance with the previously
noted requirements. Specifically, data are being curated from public domain
sources and organised using data collection templates based upon a proposal for
a global data exchange standard: ISA-TAB-Nano [2,3]. In order to facilitate
their use for modelling and, in particular, their integration with other
datasets for future modelling efforts, it is essential that the data are
recorded in a standardised fashion. To achieve this objective, the data
collection templates being employed record (meta)data using terms linked to
ontologies wherever possible. These ontology terms are being retrieved via the
BioPortal online resource [4]. Moreover, it is important that modellers are
able to assess the quality of (subsets of) the available data. To facilitate
this, proposals for assigning data quality scores are being developed. Finally,
an overview of the potential usefulness for modelling of some public domain
sources, for selected endpoints, will be presented based upon a recent survey
of the scientific literature.</p><p>
<br></p><p> The research leading
to these results has received funding from the European Union Seventh Framework
Programme [FP7/2007-2013] under grant agreement n° 309837 (NanoPUZZLES project)
and from the NanoBRIDGES project (FP7-PEOPLE-2011-IRSES, Grant Agreement no.
295128).</p><ol><li><p>Winkler, D.A..; Mombelli, E.; Pietroiusti, A.;
Tran, L.; Worth, A.; Fadeel, B.; McCall, M.J. <i>Toxicology</i>, <i>313</i>, <b>2013</b>, 15-23.</p></li><li><p>Thomas, D.G.; Gaheen, S.; Harper, S.L.; Fritts,
M.; Klaessig, F.; Hahn-Dantona, E.; Paik, D.; Pan, S.; Staffiord, G.A.; Freund,
E.T.; Klemm, J.D.; Baker, N.A. <i>BMC
Biotechnol.</i>, <i>13</i>, <b>2013</b>, 2.</p></li><li><p>https://wiki.nci.nih.gov/display/ICR/ISA-TAB-Nano
[last accessed 9th of April 2014]</p></li><li><p>Whetzel, P.L.; Noy, N.F.; Shah, N.H.; Alexander,
P.R.; Nyulas, C.; Tudorache, T.; Musen, M.A. <i>Nucleic Acids Res.</i>, <i>39</i>, <b>2011</b>, W541-W545.</p></li></ol><p>
<br></p
