AIMC Topic: Drosophila melanogaster

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Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics.

Nature methods
Keypoint tracking algorithms can flexibly quantify animal movement from videos obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into discrete actions. This challenge is particularly acute becau...

Inference of Essential Genes of the Parasite via Machine Learning.

International journal of molecular sciences
Over the years, comprehensive explorations of the model organisms (elegant worm) and (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive func...

A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot.

Biochemical and biophysical research communications
To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidi...

Automated assessment of cardiac dynamics in aging and dilated cardiomyopathy Drosophila models using machine learning.

Communications biology
The Drosophila model is pivotal in deciphering the pathophysiological underpinnings of various human ailments, notably aging and cardiovascular diseases. Cutting-edge imaging techniques and physiology yield vast high-resolution videos, demanding adva...

Behavioral toxicological tracking analysis of Drosophila larvae exposed to polystyrene microplastics based on machine learning.

Journal of environmental management
Microplastics, as a pivotal concern within plastic pollution, have sparked widespread apprehension due to their ubiquitous presence. Recent research indicates that these minuscule plastic particles may exert discernible effects on the locomotor capab...

Machine learning reveals the control mechanics of an insect wing hinge.

Nature
Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolution of active flight. Unlike pterosaurs, birds and bats, the wings of insects did not evolve from legs, but are novel structures that are attached to th...

Cell-type-directed design of synthetic enhancers.

Nature
Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes. It has been a long-standing goal in the field to decode the regulatory logic of an enhan...

Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo.

Nature
Enhancers control gene expression and have crucial roles in development and homeostasis. However, the targeted de novo design of enhancers with tissue-specific activities has remained challenging. Here we combine deep learning and transfer learning t...

A deep learning analysis of body kinematics during magnetically tethered flight.

Journal of neurogenetics
Flying rely on their vision to detect visual objects and adjust their flight course. Despite their robust fixation on a dark, vertical bar, our understanding of the underlying visuomotor neural circuits remains limited, in part due to difficulties i...

I-DNAN6mA: Accurate Identification of DNA N-Methyladenine Sites Using the Base-Pairing Map and Deep Learning.

Journal of chemical information and modeling
The recent discovery of numerous DNA N-methyladenine (6mA) sites has transformed our perception about the roles of 6mA in living organisms. However, our ability to understand them is hampered by our inability to identify 6mA sites rapidly and cost-ef...