AIMC Topic: Drosophila melanogaster

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FLYNC: a machine-learning-driven framework for discovering long noncoding RNAs in Drosophila melanogaster.

NAR genomics and bioinformatics
Noncoding RNAs have increasingly recognized roles in critical molecular mechanisms of disease. However, the noncoding genome of Drosophila melanogaster, one of the most powerful disease model organisms, has been understudied. Here, we present FLYNC-F...

Machine Learning for Separating Dopamine and Octopamine Electrochemical Signals in Drosophila.

Analytical chemistry
, the fruit fly, uses the neurotransmitters dopamine and octopamine to mediate learning, enabling adaptive behaviors such as reward seeking and punishment avoidance. Their colocalization in the mushroom bodies makes it challenging to study their indi...

DANCE provides an open-source and low-cost approach to quantify aggression and courtship in .

eLife
Quantifying animal behavior is pivotal for identifying the neuronal and genetic mechanisms involved. Computational approaches have enabled automated analysis of complex behaviors such as aggression and courtship in . However, existing approaches rely...

Differential modulation of feedforward inhibition reflects topographic organization in the olfactory system.

Nature communications
The nervous system flexibly processes information under different conditions. To do this, neural networks frequently rely on uniform expression of modulatory receptors by distinct classes of neurons to fine tune the computations supported by each neu...

Maturation of GABAergic signalling times the opening of a critical period in Drosophila melanogaster.

Scientific reports
Critical periods (CPs) during the development of neural networks are widely documented. Activity manipulation during open CPs leads to debilitating effects to the mature neural network. Detailed understanding of the contribution of CPs to network dev...

Three-dimensional ultrastructural characterization of Drosophila melanogaster hygrosensilla across humidity conditions.

PloS one
Understanding how organisms detect environmental humidity remains a fundamental problem in sensory biology. While specialised sensory neurons in insect antennae can detect changes in humidity, the mechanism underlying this ability is not fully unders...

VacQuant: a tool to quantify neurodegeneration and associated vacuolation in brain tissue.

Fly
Neurodegenerative diseases are devastating conditions characterized by progressive cognitive decline with few available treatments. Neurodegeneration can be quantified in vertebrate and invertebrate models of disease by analysis of vacuolation - the ...

Deep learning-based high-resolution time inference for deciphering dynamic gene regulation from fixed embryos.

Nature communications
Embryo development is driven by the spatiotemporal dynamics of complex gene regulatory networks. Uncovering these dynamics requires simultaneous tracking of multiple fluctuating molecular species over time, which exceeds the capabilities of tradition...

A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.

eLife
Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble into functional neural networks. Studies investigating nervous system development in model systems have only focused on select regions of the CNS due t...

Hybrid neural networks in the mushroom body drive olfactory preference in .

Science advances
In , olfactory encoding in the mushroom body (MB) involves thousands of Kenyon cells (KCs) processing inputs from hundreds of projection neurons (PNs). Recent data challenge the notion of random PN-to-KC connectivity, revealing preferential connectio...