scholarly journals Automated analysis of internally programmed grooming behavior in Drosophila using a k-nearest neighbors classifier

2017 ◽  
Author(s):  
Bing Qiao ◽  
Chiyuan Li ◽  
Victoria W. Allen ◽  
Mimi M. Shirasu-Hiza ◽  
Sheyum Syed
Keyword(s):  
Nearest Neighbors ◽  
Automated Analysis ◽  
Fruit Fly ◽  
Grooming Behavior ◽  
K Nearest Neighbors ◽  
Daily Behavior ◽  
Dual Control Model ◽  
Regulatory Model

AbstractDespite being pervasive, the control of programmed grooming is poorly understood. We have addressed this gap in knowledge by developing a high-throughput platform that allows long-term detection of grooming in the fruit fly Drosophila melanogaster. Automatic classification of daily behavior shows flies spend 30% of their active time grooming. We show that a large proportion of this behavior is driven by two major internal programs. One of these programs is the circadian clock that modulates rhythms in daily grooming. The second program depends on cycle and clock and regulates the amount of time flies spend grooming. This emerging dual control model of programmed grooming in which one regulator controls the timing and another controls the duration, resembles the well-established two-process regulatory model of fly sleep. Together, our quantitative approach in Drosophila has revealed that grooming is an important internally driven behavior under the control of two regulatory programs.

scholarly journals Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Bing Qiao ◽  
Chiyuan Li ◽  
Victoria W Allen ◽  
Mimi Shirasu-Hiza ◽  
Sheyum Syed
Keyword(s):  
Nearest Neighbors ◽  
Automated Analysis ◽  
Control Model ◽  
Dual Control ◽  
Grooming Behavior ◽  
K Nearest Neighbors ◽  
The Core ◽  
Dual Control Model ◽  
Regulatory Model

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 the timing of grooming and involves the core circadian clock components cycle, clock, and period. The second program regulates the duration of grooming and, while dependent on cycle and clock, appears to be independent of period. This emerging dual control model in which one program controls timing and another controls duration, resembles the two-process regulatory model of sleep. Together, our quantitative approach presents the opportunity for further dissection of mechanisms controlling long-term grooming in Drosophila.

Classification of Shark Behaviors using K-Nearest Neighbors

2019 ◽  
Author(s):  
Sainesh Karan ◽  
Emily N Meese ◽  
Yu Yang ◽  
Hen-Geul Yeh ◽  
Christopher G Lowe ◽  
...  
Keyword(s):  
Nearest Neighbors ◽  
K Nearest Neighbors

Improvement of Classification of Shark Behaviors using K-Nearest Neighbors

2020 ◽  
Author(s):  
Ibrahim M Ali ◽  
Calvin J Lee ◽  
Hen-Geul Yeh ◽  
Sainesh Karan ◽  
Yu Yang ◽  
...  
Keyword(s):  
Nearest Neighbors ◽  
K Nearest Neighbors
Sign in / Sign up

Export Citation Format

Share Document