PLOS Computational Biology

Researchers from Japan found that macro-heterogeneity (the presence of multiple cell types) and micro-heterogeneity (variability in cell behavior within a cell type) are crucial for muscle breakdown and rearrangement in the pupal stage of fruit fly development. Computational modeling of cell interactions suggested that designing heterogenous robot swarms based on similar principles could improve their ability to multitask.

Bioengineers formulated a mathematical model that clarified the importance of bat ear motions in direction detection, making way for lean, mean sonar navigation machines.

Researchers develop a ground-breaking model to estimate bait vaccination effectiveness in wild animals based on the proportion of immunized animals in a population and the number of vaccine applications.

Chaos theory improves understanding of Arctic narwhal behavior, with the aim of helping efforts to protect this vulnerable species.

Atomic force microscopy (AFM) allows to visualize the dynamics of single biomolecules during their functional activity. All observations are, however, restricted to regions accessible by a fairly big probing tip during scanning. Hence, AFM images only the biomolecular surface with limited spatial resolution, missing important information required for a detailed understanding of the observed phenomena.

Atomic force microscopy (AFM) allows to obtain images and movies showing proteins at work, however with limited resolution. The developed BioAFMviewer software opens the opportunity to use the enormous amount of available high-resolution protein data to better understand experiments. Within an interactive interface with rich functionality, the BioAFMviewer computationally emulates tip-scanning of any biomolecular structure to generate simulated AFM graphics and movies. They greatly help in the interpretation of e.g., high-speed AFM observations.

In a recent study from Hiroshima University, researchers turned to mathematics to predict hive patterns in humans.