https://hal-pasteur.archives-ouvertes.fr/pasteur-01799353/document

TrackMate: An open and extensible platform for single-particle tracking.

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Principles Of Optics Electromagnetic Theory Of Propagation Interference And Diffraction Of Light

The spatial regulation of protein translation is an efficient way to create functional and structural asymmetries in cells. Recent research has furthered our understanding of how individual cells spatially organize protein synthesis, by applying innovative technology to characterize the relationship between mRNAs and their regulatory proteins, single-mRNA trafficking dynamics, physiological effects of abrogating mRNA localization in vivo and for endogenous mRNA labelling. The implementation of new imaging technologies has yielded valuable information on mRNA localization, for example, by observing single molecules in tissues. The emerging movements and localization patterns of mRNAs in morphologically distinct unicellular organisms and in neurons have illuminated shared and specialized mechanisms of mRNA localization, and this information is complemented by transgenic and biochemical techniques that reveal the biological consequences of mRNA mislocalization.

In the right place at the right time: visualizing and understanding mRNA localization

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.

/pdf/an-objective-comparison-of-cell-tracking-algorithms-oghb4db19g.pdf

An objective comparison of cell-tracking algorithms

Optical microscopy has for centuries been a key tool to study living cells with minimum invasiveness The advent of single molecule techniques over the past two decades has revolutionized the field of cell biology by providing a more quantitative picture of the complex and highly dynamic organization of living systems Amongst these techniques, single particle tracking (SPT) has emerged as a powerful approach to study a variety of dynamic processes in life sciences SPT provides access to single molecule behavior in the natural context of living cells, thereby allowing a complete statistical characterization of the system under study In this review we describe the foundations of SPT together with novel optical implementations that nowadays allow the investigation of single molecule dynamic events with increasingly high spatiotemporal resolution using molecular densities closer to physiological expression levels We outline some of the algorithms for the faithful reconstruction of SPT trajectories as well as data analysis, and highlight biological examples where the technique has provided novel insights into the role of diffusion regulating cellular function The last part of the review concentrates on different theoretical models that describe anomalous transport behavior and ergodicity breaking observed from SPT studies in living cells

https://iopscience.iop.org/article/10.1088/0034-4885/78/12/124601/pdf

A review of progress in single particle tracking: from methods to biophysical insights.

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

/pdf/objective-comparison-of-particle-tracking-methods-2lwbdb20ki.pdf

Yuh-Show Tsai

Papers

Objective comparison of particle tracking methods