Visual and Semantic Enrichment of Analytical Chemistry Literature Searches by Combining Text Mining and Computational Chemistry

Abstract

The open-access scientific literature contains a wealth of information for meaningful text mining. However, this information is not always easy to retrieve. This technical note addresses the problem by a new flexible method combining in a single workflow existing resources for literature searches, text mining, and large-scale prediction of physicochemical and biological properties. The results are visualized as virtual mass spectra, chromatograms, or images in styles new to text mining but familiar to analytical chemistry. The method is demonstrated on comparisons of analytical-chemistry techniques and semantically enriched searches for proteins and their activities, but it may also be of general utility in experimental design, drug discovery, chemical syntheses, business intelligence, and historical studies. The method is realized in shareable scientific workflows using only freely available data, services, and software that scale to millions of publications and named chemical entities in the literature.

Non-Uniform Gaussian Blur of Hexagonal Bins in Cartesian Coordinates

“…Europe PMC for scientific papers mentioning particular techniques from analytical chemistry in their section-tagged materials and methods sections (Palmblad, 2019). Hexagonal about the applicability of the analytical techniques: The sliders for adjusting the blurring and saturation improve the user experience and help create clear visualizations.…”

“…However, in one of our use cases, based on previous work (Palmblad, 2019), the two dimensions do not represent spatial locations as in an map or image, but two different physical variables, with different underlying uncertainties. To smooth the histogram and visualize these uncertainties, we have to use the original physical dimensions or coordinates.…”