ArticlePloS one2014
QuantWorm: a comprehensive software package for Caenorhabditis elegans phenotypic assays.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
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- Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity.PLoS computational biology · 2026Article
- High-throughput adult Caenorhabditis elegans viability monitoring system.Scientific reports · 2026Article
- High-Throughput Toxicity Screening withEnvironmental science & technology · 2026Review
- FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images.PloS one · 2025Article
- Detection of the Effects of Root Exudates (Diffusates) on Nematode Hatching and Attraction.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Deep learning for robust and flexible tracking in behavioral studies for C. elegans.PLoS computational biology · 2022Article
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- Small flexible automated system for monitoring Caenorhabditis elegans lifespan based on active vision and image processing techniques.Scientific reports · 2021Article
- High-throughput behavioral screen in C. elegans reveals Parkinson's disease drug candidates.Communications biology · 2021Article
- Plant and fungal products that extend lifespan inMicrobial cell (Graz, Austria) · 2020Review
- Improving lifespan automation for Caenorhabditis elegans by using image processing and a post-processing adaptive data filter.Scientific reports · 2020Article
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- Digging deeper: methodologies for high-content phenotyping in Caenorhabditis elegans.Lab animal · 2019Review
- Transcriptomics-Based Screening Identifies Pharmacological Inhibition of Hsp90 as a Means to Defer Aging.Cell reports · 2019Article
- Mass Surveilance ofSensors (Basel, Switzerland) · 2019Article
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- Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.BMC pharmacology & toxicology · 2018Article
- WorMachine: machine learning-based phenotypic analysis tool for worms.BMC biology · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Phenotypic assays are crucial in genetics; however, traditional methods that rely on human observation are unsuitable for quantitative, large-scale experiments. Furthermore, there is an increasing need for comprehensive analyses of multiple phenotypes to provide multidimensional information. Here we developed an automated, high-throughput computer imaging system for quantifying multiple Caenorhabditis elegans phenotypes. Our imaging system is composed of a microscope equipped with a digital camera and a motorized stage connected to a computer running the QuantWorm software package. Currently, the software package contains one data acquisition module and four image analysis programs: WormLifespan, WormLocomotion, WormLength, and WormEgg. The data acquisition module collects images and videos. The WormLifespan software counts the number of moving worms by using two time-lapse images; the WormLocomotion software computes the velocity of moving worms; the WormLength software measures worm body size; and the WormEgg software counts the number of eggs. To evaluate the performance of our software, we compared the results of our software with manual measurements. We then demonstrated the application of the QuantWorm software in a drug assay and a genetic assay. Overall, the QuantWorm software provided accurate measurements at a high speed. Software source code, executable programs, and sample images are available at www.quantworm.org. Our software package has several advantages over current imaging systems for C. elegans. It is an all-in-one package for quantifying multiple phenotypes. The QuantWorm software is written in Java and its source code is freely available, so it does not require use of commercial software or libraries. It can be run on multiple platforms and easily customized to cope with new methods and requirements.
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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.