This analysis describes the results of three Cell Tracking Challenge editions for examining the performance of cell segmentation and tracking algorithms and provides practical feedback for users and developers. We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

Dynamic Assembly: Structural characterization of protein complexes has yielded significant insight into biological function; however, most structural techniques require stable, homogenous samples. This presents a challenge in characterizing transient signaling complexes. Herzog et al. (p. 1348 ) used chemical cross-linking and mass spectroscopy (XL-MS) to characterize the modular and dynamic interaction network involving phosphatase 2A (PP2A), which interacts with tens of regulatory and adaptor proteins in diverse signaling pathways. They found 176 interprotein and 569 intraprotein distance restraints that delineated the topology of the network. The study establishes the importance of XL-MS in the suite of structural methods used to characterize dynamic assemblies.