The universality of the new methodology is demonstrated using five standard data sets from different scientific fields. Its efficiency in cheminformatics and QSAR modelling is shown with three use cases: proteomics data for surface-modified gold nanoparticles, nano-metal oxides descriptor data, and molecular descriptors for acute aquatic toxicity data.
Nanomaterials are small and the small size and corresponding large surface area of nanomaterials confers specific properties, making these materials desirable for various applications, not least in medicine. However, it is pertinent to ask whether size is the only property that matters for the desirable or detrimental effects of nanomaterials?
We demonstrate the approach of adopting an ontology-supported data model, describing the materials and measurements. The data sources supported include diverse formats (ISA-Tab, OECD Harmonized Templates, custom spreadsheet templates, various databases provided by consortia members). Besides retaining the data provenance, the focus on measurements provides insights into how to reuse the chemical structure database tools for nanomaterials characterization and safety.