Evidence map›Paper›PMID 41568751›Full record

ArticleDisease models & mechanisms2026

A Segment Anything Model-based tool for semi-automated behavioural analysis of Drosophila and other model organisms.

Sarah Mele, Joshua Millward, Long Nguyen, Natasha Ruth, Jemma Gasperoni, Sebastian Dworkin, Zhen He, Travis K Johnson

Abstract read
In one paragraph

Article in Disease models & mechanisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sarah MeleDepartment of Biochemistry and Chemistry, and La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0009-0008-2174-2544
Joshua MillwardSchool of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0000-0002-6374-1426
Long NguyenSchool of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia.
Natasha RuthDepartment of Biochemistry and Chemistry, and La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC 3086, Australia.
Jemma GasperoniDepartment of Biochemistry and Chemistry, and La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0000-0001-8133-3242
Sebastian DworkinDepartment of Microbiology, Anatomy, Physiology and Pharmacology, and La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0000-0001-5828-9992
Zhen HeSchool of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0000-0003-0302-5775
Travis K JohnsonDepartment of Biochemistry and Chemistry, and La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC 3086, Australia.ORCID 0000-0001-6846-9313

Funding

Archie's EmbraceAustralian Research Council 220100023Australian Research Council FT220100023La Trobe UniversityNational Health and Medical Research Council 2038384National Health and Medical Research Council APP2038384
6 · The paper itself

Abstract

Quantitative behavioural analysis is a powerful approach for linking genotype to phenotype, but many existing tools require specialised hardware, extensive preprocessing or coding expertise. We present Segment Anything Model for Behavioural Analysis (SAMBA), an open-access, Google Colab-based pipeline that harnesses the Segment Anything Model 2 (SAM2) for accurate, semi-automated tracking without thresholding or background subtraction. With minimal user input, SAMBA extracts movement parameters, detects behavioural states and supports batch processing. Validating SAMBA in three Drosophila melanogaster models of human neurological disease revealed impaired locomotion, reduced speed and altered decision-making. We further demonstrated adaptability to adult Drosophila and larval zebrafish, underscoring its cross-species utility. By combining foundation-model segmentation with an accessible interface, SAMBA lowers technical barriers to analysing motor pattern defects and is readily extendable to diverse model organisms, life stages and experimental paradigms. This flexibility positions SAMBA as a valuable platform for accelerating disease mechanism studies, genetic screens and preclinical testing.

Indexed as

Behavior, AnimalDrosophila melanogasterSoftwareAnimalsAutomationHumansLarvaLocomotionPhenotypeZebrafishBehaviourDanio rerioDrosophila melanogasterSAM2 modelSegmentationTrackingZebrafish

Identifiers

PMID41568751
PMCPMC12964350

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.