RESUMEN
Background: Unicorn™ software on Äkta liquid chromatography instruments outputs chromatography profiles of purified biological macromolecules. While the plots generated by the instrument software are very helpful to inspect basic chromatogram properties, they lack a range of useful annotation, customization and export options. Methods: We use the R Shiny framework to build an interactive app that facilitates the interpretation of chromatograms and the generation of figures for publications. Results: The app allows users to fit a baseline, to highlight selected fractions and elution volumes inside or under the plot (e.g. those used for downstream biochemical/biophysical/structural analysis) and to zoom into the plot. The app is freely available at https://ChromatoShiny.bio.ed.ac.uk. Conclusions: It requires no programming experience, so we anticipate that it will enable chromatography users to create informative, annotated chromatogram plots quickly and simply.
RESUMEN
The integration of theory and data drives progress in science, but a persistent barrier to such integration in ecology and evolutionary biology is that theory is often developed and expressed in the form of mathematical models that can feel daunting and inaccessible for students and empiricists with variable quantitative training and attitudes towards math. A promising way to make mathematical models more approachable is to embed them into interactive tools with which one can visually evaluate model structures and directly explore model outcomes through simulation. To promote such interactive learning of quantitative models, we developed EcoEvoApps, a collection of free, open-source, and multilingual R/Shiny apps that include model overviews, interactive model simulations, and code to implement these models directly in R. The package currently focuses on canonical models of population dynamics, species interactions, and landscape ecology. These apps help illustrate fundamental results from theoretical ecology and can serve as valuable teaching tools in classroom settings. We present data from student surveys which show that students rate these apps as useful learning tools, and that using interactive apps leads to substantial gains in students' interest and confidence in working with mathematical models. This points to the potential for interactive activities to make theoretical models more accessible to a wider audience, and thus facilitate the feedback between theory and data across ecology and evolutionary biology.