ArticlePloS one2013
Track-a-worm, an open-source system for quantitative assessment of C. elegans locomotory and bending behavior.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
36 citing papers in PubMed, 70 citations in OpenAlex.
- Deep-Pose-Tracker: an automated behavioural analysis framework for Caenorhabditis elegans.Scientific reports · 2026Article
- Automated analysis of C. elegans behavior by LabGym: an open-source, AI-powered platform.G3 (Bethesda, Md.) · 2026Article
- Proton signaling links epithelial sensing to neural control of host defense in C. elegans.Nature communications · 2026Article
- Maternal age modulates progeny social behavior via a small RNA-neuropeptide axis.bioRxiv : the preprint server for biology · 2026Article
- Review
- A scaffold attachment factor PHM-2 regulates synaptic transmission through SLO-2 potassium channel in C. elegans.PLoS genetics · 2026Article
- A scaffold attachment factor PHM-2 regulates synaptic transmission through SLO-2 potassium channel inbioRxiv : the preprint server for biology · 2025Article
- Automated C. elegans behavior analysis via deep learning-based detection and tracking.PLoS computational biology · 2025Article
- HarnessingSensors (Basel, Switzerland) · 2025Review
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- A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan.Scientific reports · 2025Article
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- An automated, high-resolution phenotypic assay for adult Brugia malayi and microfilaria.Scientific reports · 2024Article
- Locomotion modulates olfactory learning through proprioception in C. elegans.Nature communications · 2023Article
- Fast detection of slender bodies in high density microscopy data.Communications biology · 2023Article
- Automated recognition and analysis of body bending behavior in C. elegans.BMC bioinformatics · 2023Article
- A Compact Imaging Platform for ConductingLife (Basel, Switzerland) · 2023Article
- Automated recognition and analysis of head thrashes behavior in C. elegans.BMC bioinformatics · 2022Article
- A Markerless Pose Estimator Applicable to Limbless Animals.Frontiers in behavioral neuroscience · 2022Article
- GABAergic motor neurons bias locomotor decision-making in C. elegans.Nature communications · 2020Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A major challenge of neuroscience is to understand the circuit and gene bases of behavior. C. elegans is commonly used as a model system to investigate how various gene products function at specific tissue, cellular, and synaptic foci to produce complicated locomotory and bending behavior. The investigation generally requires quantitative behavioral analyses using an automated single-worm tracker, which constantly records and analyzes the position and body shape of a freely moving worm at a high magnification. Many single-worm trackers have been developed to meet lab-specific needs, but none has been widely implemented for various reasons, such as hardware difficult to assemble, and software lacking sufficient functionality, having closed source code, or using a programming language that is not broadly accessible. The lack of a versatile system convenient for wide implementation makes data comparisons difficult and compels other labs to develop new worm trackers. Here we describe Track-A-Worm, a system rich in functionality, open in source code, and easy to use. The system includes plug-and-play hardware (a stereomicroscope, a digital camera and a motorized stage), custom software written to run with Matlab in Windows 7, and a detailed user manual. Grayscale images are automatically converted to binary images followed by head identification and placement of 13 markers along a deduced spline. The software can extract and quantify a variety of parameters, including distance traveled, average speed, distance/time/speed of forward and backward locomotion, frequency and amplitude of dominant bends, overall bending activities measured as root mean square, and sum of all bends. It also plots worm travel path, bend trace, and bend frequency spectrum. All functionality is performed through graphical user interfaces and data is exported to clearly-annotated and documented Excel files. These features make Track-A-Worm a good candidate for implementation in other labs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.