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Drosophila melanogaster

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Deep learning for rapid analysis of cell divisions in vivo during epithelial morphogenesis and repair.

eLife
Cell division is fundamental to all healthy tissue growth, as well as being rate-limiting in the tissue repair response to wounding and during cancer progression. However, the role that cell divisions play in tissue growth is a collective one, requir...

A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity.

Nucleic acids research
Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene t...

Sex dimorphism and hormesis response to polystyrene microplastic exposure in kinematics and metabolism of Drosophila model based on deep learning.

Journal of environmental management
The emergence of microplastics (MPs) has become a significant focus of environmental pollution, prompting widespread concern regarding its potential toxicity and impact on the environment and organisms. Recent research indicates notable alterations i...

Comparing statistical learning methods for complex trait prediction from gene expression.

PloS one
Accurate prediction of complex traits is an important task in quantitative genetics. Genotypes have been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regression methods, dimension reduction me...

Deep learning-driven behavioral analysis reveals adaptive responses in Drosophila offspring after long-term parental microplastic exposure.

Journal of environmental management
Microplastics are widely distributed in the environment and pose potential hazards to organisms. However, our understanding of the transgenerational effects of microplastics on terrestrial organisms remains limited. In this study, we focused on the m...

FlyVISTA, an integrated machine learning platform for deep phenotyping of sleep in .

Science advances
There is great interest in using genetically tractable organisms such as to gain insights into the regulation and function of sleep. However, sleep phenotyping in has largely relied on simple measures of locomotor inactivity. Here, we present FlyVI...

Neural network conditioned to produce thermophilic protein sequences can increase thermal stability.

Scientific reports
This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. The model, trained on over 4 mill...

The fruit fly, , as a microrobotics platform.

Proceedings of the National Academy of Sciences of the United States of America
Engineering small autonomous agents capable of operating in the microscale environment remains a key challenge, with current systems still evolving. Our study explores the fruit fly, , a classic model system in biology and a species adept at microsca...

Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.

Genome research
Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F crosses with extensive genetic diversity...

Machine Learning Scoring Reveals Increased Frequency of Falls Proximal to Death in Drosophila melanogaster.

The journals of gerontology. Series A, Biological sciences and medical sciences
Falls are a significant cause of human disability and death. Risk factors include normal aging, neurodegenerative disease, and sarcopenia. Drosophila melanogaster is a powerful model for study of normal aging and for modeling human neurodegenerative ...