ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018
Powerful and interpretable behavioural features for quantitative phenotyping of
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
56 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
- Development of a universal imaging "phenome" using shape, appearance and motion (SAM) features and the SAM Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Deep-Pose-Tracker: an automated behavioural analysis framework for Caenorhabditis elegans.Scientific reports · 2026Article
- Application ofBiomolecules & therapeutics · 2026Review
- Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity.PLoS computational biology · 2026Article
- Continuous negative autoregulation fine-tunes dosage-sensitive transcription factor expression to maintain post-mitotic neuron identity.bioRxiv : the preprint server for biology · 2026Article
- High-Throughput Toxicity Screening withEnvironmental science & technology · 2026Review
- Autocrine feedback maintains homeostatic neuropeptide expression in a peptidergic hub neuron.bioRxiv : the preprint server for biology · 2026Article
- Tau clearance reverses touch neuron dysfunction in both young and agedJournal of Alzheimer's disease : JAD · 2026Article
- Article
- Guide frames improve centerline estimation of complex postures in WormTracer.microPublication biology · 2026Article
- Cell type-specific functions of the PBAF chromatin-remodeling complex in neuronal diversification.Nature communications · 2025Article
- Cohesin forms fountains at active enhancers in C. elegans.Nature communications · 2025Article
- Automated C. elegans behavior analysis via deep learning-based detection and tracking.PLoS computational biology · 2025Article
- High-throughput behavioural phenotyping of 25 C. elegans disease models including patient-specific mutations.BMC biology · 2025Article
- Article
- High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing.Scientific reports · 2025Article
- Identification of a key peptide cyclase for novel cyclic peptide discovery in Pseudostellaria heterophylla.Plant communications · 2025Article
- Neuroendocrine Control of Synaptic Transmission by PHAC-1 inThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Behaviour is a sensitive and integrative readout of nervous system function and therefore an attractive measure for assessing the effects of mutation or drug treatment on animals. Video data provide a rich but high-dimensional representation of behaviour, and so the first step of analysis is often some form of tracking and feature extraction to reduce dimensionality while maintaining relevant information. Modern machine-learning methods are powerful but notoriously difficult to interpret, while handcrafted features are interpretable but do not always perform as well. Here, we report a new set of handcrafted features to compactly quantify
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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.