Evidence map›Paper›PMID 19270697›Full record

ArticleNature methods2009

Automated monitoring and analysis of social behavior in Drosophila.

Heiko Dankert, Liming Wang, Eric D Hoopfer, David J Anderson, Pietro Perona

Abstract read
In one paragraph

Article in Nature methods, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 185 papers.

0numbers the graph read from it
0cells of the map it votes in
185citing 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

185 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Autobehaver: An AI-Based Pipeline for Animal Behavior Analysis.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Movement and Dispersion Parameters Characterizing the Group Behavior ofAnimals : an open access journal from MDPI · 2025
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Investigating the Neural Control of Social Behavior inJournal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2025
    Article
  18. The impact of machine learning on ethological neuroscience.Frontiers in behavioral neuroscience · 2025
    Review
  19. Article
  20. Insects · 2024
    Review

125 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Heiko DankertHoward Hughes Medical Institute, California Institute of Technology, Pasadena, USA.
Liming Wang
Eric D Hoopfer
David J Anderson
Pietro Perona

Funding

CRCNS: Automated Behavior Analysis for Model Genetic OrganismR01DA022777 · NIDA · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI PERONA, PIETRO · 2006 to 2010
$1.3M
Howard Hughes Medical InstituteNIDA NIH HHS R01 DA022777
6 · The paper itself

Abstract

We introduce a method based on machine vision for automatically measuring aggression and courtship in Drosophila melanogaster. The genetic and neural circuit bases of these innate social behaviors are poorly understood. High-throughput behavioral screening in this genetically tractable model organism is a potentially powerful approach, but it is currently very laborious. Our system monitors interacting pairs of flies and computes their location, orientation and wing posture. These features are used for detecting behaviors exhibited during aggression and courtship. Among these, wing threat, lunging and tussling are specific to aggression; circling, wing extension (courtship 'song') and copulation are specific to courtship; locomotion and chasing are common to both. Ethograms may be constructed automatically from these measurements, saving considerable time and effort. This technology should enable large-scale screens for genes and neural circuits controlling courtship and aggression.

Indexed as

Artificial IntelligenceSocial BehaviorAnimalsBehavior, AnimalDrosophila melanogasterHumansImage Interpretation, Computer-AssistedMonitoring, PhysiologicMovementPattern Recognition, AutomatedPosture

Identifiers

PMID19270697
PMCPMC2679418

What OpenQuestion holds

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Registered trials

None linked

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.