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Drosophila melanogaster

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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...

High-throughput genetic manipulation of multicellular organisms using a machine-vision guided embryonic microinjection robot.

Genetics
Microinjection is a technique used for transgenesis, mutagenesis, cell labeling, cryopreservation, and in vitro fertilization in multiple single and multicellular organisms. Microinjection requires specialized skills and involves rate-limiting and la...

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...

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...

Learning meaningful representation of single-neuron morphology via large-scale pre-training.

Bioinformatics (Oxford, England)
SUMMARY: Single-neuron morphology, the study of the structure, form, and shape of a group of specialized cells in the nervous system, is of vital importance to define the type of neurons, assess changes in neuronal development and aging and determine...

Deep learning reveals a damage signalling hierarchy that coordinates different cell behaviours driving wound re-epithelialisation.

Development (Cambridge, England)
One of the key tissue movements driving closure of a wound is re-epithelialisation. Earlier wound healing studies describe the dynamic cell behaviours that contribute to wound re-epithelialisation, including cell division, cell shape changes and cell...

Ense-i6mA: Identification of DNA N-Methyladenine Sites Using XGB-RFE Feature Selection and Ensemble Machine Learning.

IEEE/ACM transactions on computational biology and bioinformatics
DNA N-methyladenine (6mA) is an important epigenetic modification that plays a vital role in various cellular processes. Accurate identification of the 6mA sites is fundamental to elucidate the biological functions and mechanisms of modification. How...