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Nemo: a computational tool for analyzing nematode locomotion

George D Tsibidis1* and Nektarios Tavernarakis2

Author affiliations

1 Institute of Electronic Structure and Laser, Foundation for Research and Technology, PO Box 1385, Vasilika Vouton, 71110 Heraklion, Crete, Greece

2 Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, PO Box 1385, Vasilika Vouton, 71110 Heraklion, Crete, Greece

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Citation and License

BMC Neuroscience 2007, 8:86  doi:10.1186/1471-2202-8-86

Published: 17 October 2007



The nematode Caenorhabditis elegans responds to an impressive range of chemical, mechanical and thermal stimuli and is extensively used to investigate the molecular mechanisms that mediate chemosensation, mechanotransduction and thermosensation. The main behavioral output of these responses is manifested as alterations in animal locomotion. Monitoring and examination of such alterations requires tools to capture and quantify features of nematode movement.


In this paper, we introduce Nemo (

vement), a computationally efficient and robust two-dimensional object tracking algorithm for automated detection and analysis of C. elegans locomotion. This algorithm enables precise measurement and feature extraction of nematode movement components. In addition, we develop a Graphical User Interface designed to facilitate processing and interpretation of movement data. While, in this study, we focus on the simple sinusoidal locomotion of C. elegans, our approach can be readily adapted to handle complicated locomotory behaviour patterns by including additional movement characteristics and parameters subject to quantification.


Our software tool offers the capacity to extract, analyze and measure nematode locomotion features by processing simple video files. By allowing precise and quantitative assessment of behavioral traits, this tool will assist the genetic dissection and elucidation of the molecular mechanisms underlying specific behavioral responses.