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A network approach to discerning the identities of C. elegans in a free moving population

机译:一种在自由移动人口中辨别秀丽隐杆线虫的身份的网络方法

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The study of C. elegans has led to ground-breaking discoveries in gene-function, neuronal circuits, and physiological responses. Subtle behavioral phenotypes, however, are often difficult to measure reproducibly. We have developed an experimental and computational infrastructure to simultaneously record and analyze the physical characteristics, movement, and social behaviors of dozens of interacting free-moving nematodes. Our algorithm implements a directed acyclic network that reconstructs the complex behavioral trajectories generated by individual C. elegans in a free moving population by chaining hundreds to thousands of short tracks into long contiguous trails. This technique allows for the high-throughput quantification of behavioral characteristics that require long-term observation of individual animals. The graphical interface we developed will enable researchers to uncover, in a reproducible manner, subtle time-dependent behavioral phenotypes that will allow dissection of the molecular mechanisms that give rise to organism-level behavior.
机译:C.杆杆线的研究导致基因功能,神经元电路和生理反应中的接地发现。然而,微妙的行为表型通常难以可重复测量。我们开发了一个实验和计算基础设施,同时记录和分析数十个互动的自由移动线虫的物理特征,运动和社会行为。我们的算法实现了一条定向的非循环网络,该网络通过将数百到数千个短轨道链接到长期连续的小径中,重建由自由移动人口中的单个C.杆状杆的复杂行为轨迹。该技术允许需要长期观察单个动物的行为特征的高通量量化。我们开发的图形界面将使研究人员能够以可重复的方式揭示微妙的时间依赖性行为表型,这将允许解剖产生生物水平行为的分子机制。

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