Visualization of Multidimensional Data for Nanomaterial Characterization

For the purpose of visualization, several techniques can be used to handle multidimensional data, such as parallel coordinates, heat-maps, projection, and clustering methods. This chapter presents a case study in the field of nanotoxicology and in particular of how large multidimensional data can be visually represented using structure-activity relationship (SAR) approach based on parallel coordinates. The case study includes data sets of 18 engineered nanomaterials (ENMs), each of which was characterized in terms of its physicochemical properties such as particle size, size distribution, surface area, morphology, metal content, reactivity, and free radical generation. In addition, a range of toxicity tests were conducted for the same panel of ENMs to determine their acute in vitro toxicity. More information on parallel coordinate method is discussed in the chapter, so as to give the reader sufficient knowledge to understand the case study.