ArticlePLoS computational biology2021
WormPose: Image synthesis and convolutional networks for pose estimation in C. elegans.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of artificial intelligence use in behavioral analysis of invertebrate and larval model organisms: methods, applications and future recommendations.Frontiers in artificial intelligence · 2026Pooled it
- 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
- Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity.PLoS computational biology · 2026Article
- A dataset of fine-grained zebrafish interactions in health and disease.Scientific data · 2026Article
- High-Throughput Toxicity Screening withEnvironmental science & technology · 2026Review
- Guide frames improve centerline estimation of complex postures in WormTracer.microPublication biology · 2026Article
- Automated analysis ofbioRxiv : the preprint server for biology · 2025Article
- A neural network model enables worm tracking in challenging conditions and increases signal-to-noise ratio in phenotypic screens.PLoS computational biology · 2025Article
- High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing.Scientific reports · 2025Article
- A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan.Scientific reports · 2025Article
- Uncovering multiscale structure in the variability of larval zebrafish navigation.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A Markovian dynamics forProceedings of the National Academy of Sciences of the United States of America · 2024Article
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- Fluctuating landscapes and heavy tails in animal behavior.bioRxiv : the preprint server for biology · 2023Article
- Rapid automated 3-D pose estimation of larval zebrafish using a physical model-trained neural network.PLoS computational biology · 2023Article
- Fast detection of slender bodies in high density microscopy data.Communications biology · 2023Article
- WormSwin: Instance segmentation of C. elegans using vision transformer.Scientific reports · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An important model system for understanding genes, neurons and behavior, the nematode worm C. elegans naturally moves through a variety of complex postures, for which estimation from video data is challenging. We introduce an open-source Python package, WormPose, for 2D pose estimation in C. elegans, including self-occluded, coiled shapes. We leverage advances in machine vision afforded from convolutional neural networks and introduce a synthetic yet realistic generative model for images of worm posture, thus avoiding the need for human-labeled training. WormPose is effective and adaptable for imaging conditions across worm tracking efforts. We quantify pose estimation using synthetic data as well as N2 and mutant worms in on-food conditions. We further demonstrate WormPose by analyzing long (∼ 8 hour), fast-sampled (∼ 30 Hz) recordings of on-food N2 worms to provide a posture-scale analysis of roaming/dwelling behaviors.
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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.