"Visualize, describe, compare" - nanoinformatics approaches for material-omics

Bioinformatics and cheminformatics are established disciplines, but nanoinformatics, the development of computational tools for understanding and designing nanomaterials, is still in its infancy. In light of the new data-driven approaches for nanomaterials discovery, there is a growing need for in silico tools tailored to analyze nanomaterials datasets. This is particularly crucial for soft materials, where a crystalline structure cannot be obtained and therefore the characterization datasets are less structured, and there are no standard methods for data mining. Here we present a computational package capable of visualizing, describing, and comparing nanoparticle datasets obtained with super-resolution microscopy at the single-particle and single-molecule level. Our method allows us to: i) visualize multiparametric nanoparticle datasets to grasp material properties and heterogeneity; ii) have a quantitative evaluation of a material through a series of molecular descriptors, and iii) compare different materials quantitatively and globally, going beyond comparison of a single property. We applied this method to a library of targeted nanoparticles revealing particle heterogeneity, similarities, and correlations between the synthesis and the physicochemical properties of the different nanomaterials. Finally, we show the potential of this approach to reveal batch-to-batch variations in time and between users hidden in standard analysis.