Spot-On is an easy-to-use website that makes a rigorous and bias-corrected modeling framework for analysis of single-molecule tracking experiments available to all.

Incremental deep learning enables accurate tracking of cell lineages in 3D with a modest investment in time and effort.

A deep neural network trained on semi-synthetic data learns to quickly track and identify neurons in Caenorhabditis elegans.

TBX5 lineage tracing and high resolution single cell transcriptomics uncover the predominance of first heart field development during human-induced pluripotent stem cell cardiac differentiation.

anTraX is an algorithm and software package that facilitates automated analyses of insect social behavior in species and experimental settings that are not accessible with currently existing technology.

Being fast, memory efficient, easy to use, and with powerful integrated tools, TRex will lower barriers of entry into, and enable more ambitious approaches to, the quantitative study of behavior.

A deep learning-based pipeline was developed for extracting cellular signals flexibly from moving cells in 3D time lapse images, and it outperformed previous methods under different imaging conditions.

Single-cell tracking and cell-fate simulation suggest that low levels of p53 suppress aneuploid cell formation in unstressed cells and also reveal the dual fate of cells lacking p53 in the presence of p53-proficient cells.

The nanoscopic landscape of the membrane has a direct impact on the spatiotemporal, and likely also the signaling, dynamics of Ras proteins.

The strong limitation of human subjects in tracking two color streams simultaneously as they independently traverse color space can be attributed to attention alternating slowly and sequentially between streams.