Data from: Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier

Bing Qiao, Chiyuan Li, Victoria W. Allen, Mimi M. Shirasu-Hiza & Sheyum Syed
Despite being pervasive, the control of programmed grooming is poorly understood. We addressed this gap by developing a high-throughput platform that allows long-term detection of grooming in Drosophila melanogaster. In our method, a k-nearest neighbors algorithm automatically classifies fly behavior and finds grooming events with over 90% accuracy in diverse genotypes. Our data show that flies spend ~13% of their waking time grooming, driven largely by two major internal programs. One of these programs regulates...
1 citation reported since publication in 2019.
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11 downloads reported since publication in 2019.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
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