scholarly journals Decision letter: Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes

2018 ◽  
Keyword(s):  
Motion Sensing ◽  
Computational Framework ◽  
Cellular Motion

scholarly journals Author response: Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes

2018 ◽  
Author(s):  
Felix Y Zhou ◽  
Carlos Ruiz-Puig ◽  
Richard P Owen ◽  
Michael J White ◽  
Jens Rittscher ◽  
...  
Keyword(s):  
Author Response ◽  
Motion Sensing ◽  
Computational Framework ◽  
Cellular Motion

scholarly journals Correction: Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Felix Yuran Zhou ◽  
Carlos Ruiz-Puig ◽  
Richard P Owen ◽  
Michael J White ◽  
Jens Rittscher ◽  
...  
Keyword(s):  
Motion Sensing ◽  
Computational Framework ◽  
Cellular Motion

scholarly journals Motion Sensing Superpixels (MOSES): A systematic framework to quantify and discover cellular motion phenotypes

2018 ◽  
Author(s):  
Felix Y. Zhou ◽  
Carlos Ruiz-Puig ◽  
Richard P. Owen ◽  
Michael J. White ◽  
Jens Rittscher ◽  
...  
Keyword(s):  
Visual Motion ◽  
Cellular Interactions ◽  
Motion Sensing ◽  
Cell Sheets ◽  
Dynamic Interactions ◽  
Experimental Conditions ◽  
Boundary Formation ◽  
Analytical Tools ◽  
External Stimuli ◽  
Cellular Motion

AbstractCellular motion is fundamental in tissue development and homeostasis. There is strong interest in identifying factors that affect the interactions of cells in disease but analytical tools for robust and sensitive quantification in varying experimental conditions for large extended timelapse acquisitions is limited. We present Motion Sensing Superpixels (MOSES), a method to systematically capture diverse features of cellular dynamics. We quantify dynamic interactions between epithelial cell sheets using cell lines of the squamous and columnar epithelia in human normal esophagus, Barrett’s esophagus and esophageal adenocarcinoma and find unique boundary formation between squamous and columnar cells. MOSES also measured subtle changes in the boundary formation caused by external stimuli. The same conclusions of the 190 videos were arrived at unbiasedly with little prior knowledge using a visual motion map generated from unique MOSES motion ‘signatures’. MOSES is a versatile framework to measure, characterise and phenotype cellular interactions for high-content screens.

scholarly journals Motion sensing superpixels (MOSES) is a systematic computational framework to quantify and discover cellular motion phenotypes

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Felix Y Zhou ◽  
Carlos Ruiz-Puig ◽  
Richard P Owen ◽  
Michael J White ◽  
Jens Rittscher ◽  
...  
Keyword(s):  
Cell Tracking ◽  
Time Lapse ◽  
Cell Interactions ◽  
Motion Sensing ◽  
Computational Framework ◽  
Systematic Analysis ◽  
Drug Candidates ◽  
Cellular Processes ◽  
Motion Dynamics ◽  
Cell Cell

Correct cell/cell interactions and motion dynamics are fundamental in tissue homeostasis, and defects in these cellular processes cause diseases. Therefore, there is strong interest in identifying factors, including drug candidates that affect cell/cell interactions and motion dynamics. However, existing quantitative tools for systematically interrogating complex motion phenotypes in timelapse datasets are limited. We present Motion Sensing Superpixels (MOSES), a computational framework that measures and characterises biological motion with a unique superpixel ‘mesh’ formulation. Using published datasets, MOSES demonstrates single-cell tracking capability and more advanced population quantification than Particle Image Velocimetry approaches. From > 190 co-culture videos, MOSES motion-mapped the interactions between human esophageal squamous epithelial and columnar cells mimicking the esophageal squamous-columnar junction, a site where Barrett’s esophagus and esophageal adenocarcinoma often arise clinically. MOSES is a powerful tool that will facilitate unbiased, systematic analysis of cellular dynamics from high-content time-lapse imaging screens with little prior knowledge and few assumptions.

A Multiphysics Computational Framework for Cylindrical Battery Behavior upon Mechanical Loading Based on LS-DYNA

2019 ◽  
Vol 166 (6) ◽  
pp. A1160-A1169 ◽  
Author(s):  
Chunhao Yuan ◽  
Xiang Gao ◽  
Hin Kwan Wong ◽  
Bill Feng ◽  
Jun Xu
Keyword(s):  
Mechanical Loading ◽  
Computational Framework

Qualitative simulation and related approaches for the analysis of dynamic systems

2004 ◽  
Vol 19 (2) ◽  
pp. 93-132 ◽  
Author(s):  
HIDDE DE JONG
Keyword(s):  
Qualitative Analysis ◽  
Dynamic Systems ◽  
Quantitative Information ◽  
Simulation Methods ◽  
Science And Engineering ◽  
Computational Framework ◽  
Combinatorial Explosion ◽  
Qualitative Simulation ◽  
Qualitative Phase ◽  
Made In

Methods for qualitative simulation allow predictions on the dynamics of a system to be made in the absence of quantitative information, by inferring the range of possible qualitative behaviors compatible with the structure of the system. This article reviews QSIM and other qualitative simulation methods. It discusses two problems that have seriously compromised the application of these methods to realistic problems in science and engineering: the occurrence of spurious behavior predictions and the combinatorial explosion of the number of behavior predictions. In response to these problems, related approaches for the qualitative analysis of dynamic systems have emerged: qualitative phase-space analysis and semi-quantitative simulation. The article argues for a synthesis of these approaches in order to obtain a computational framework for the qualitative analysis of dynamic systems. This should provide a solid basis for further upscaling and for the development of model-based reasoning applications of a wider scope.

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