This review highlights recent efforts on applying electron microscopy (EM) to soft (including
biological) nanomaterials. We will show how developments of both the hardware and …

The availability of large datasets has boosted the application of machine learning in many
fields and is now starting to shape active-matter research as well. Machine learning …

Deviations from Brownian motion leading to anomalous diffusion are found in transport
dynamics from quantum physics to life sciences. The characterization of anomalous diffusion …

Individual proteins and protein complexes undergo various motion types, including free
diffusion, confinement, subdiffusion and directed motion. Different motion behaviours reflect …

Modern single-particle-tracking techniques produce extensive time-series of diffusive motion
in a wide variety of systems, from single-molecule motion in living-cells to movement …

Video microscopy has a long history of providing insight and breakthroughs for a broad
range of disciplines, from physics to biology. Image analysis to extract quantitative …

Single-particle traces of the diffusive motion of molecules, cells, or animals are by now
routinely measured, similar to stochastic records of stock prices or weather data …

It is well established that a wide variety of phenomena in cellular and molecular biology
involve anomalous transport eg the statistics for the motility of cells and molecules are …

As an optical machine learning framework, Diffractive Deep Neural Networks (D2NN) take
advantage of data-driven training methods used in deep learning to devise light–matter …

In order to study transport in complex environments, it is extremely important to determine
the physical mechanism underlying diffusion and precisely characterize its nature and …