AIMC Topic: Drosophila Proteins

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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...

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...

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...

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...

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...

Bound ion effects: Using machine learning method to study the kinesin Ncd's binding with microtubule.

Biophysical journal
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions tha...

Designer genes courtesy of artificial intelligence.

Genes & development
The core promoter determines not only where gene transcription initiates but also the transcriptional activity in both basal and enhancer-induced conditions. Multiple short sequence elements within the core promoter have been identified in different ...

Latent space of a small genetic network: Geometry of dynamics and information.

Proceedings of the National Academy of Sciences of the United States of America
The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as...