AIMC Topic: Drosophila melanogaster

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Transcriptomes of lineage-specific Drosophila neuroblasts profiled by genetic targeting and robotic sorting.

Development (Cambridge, England)
A brain consists of numerous distinct neurons arising from a limited number of progenitors, called neuroblasts in Drosophila. Each neuroblast produces a specific neuronal lineage. To unravel the transcriptional networks that underlie the development ...

Genome-Wide Detection and Analysis of Multifunctional Genes.

PLoS computational biology
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular...

Dexterous robotic manipulation of alert adult Drosophila for high-content experimentation.

Nature methods
We present a robot that enables high-content studies of alert adult Drosophila by combining operations including gentle picking; translations and rotations; characterizations of fly phenotypes and behaviors; microdissection; or release. To illustrate...

Computational algorithms to predict Gene Ontology annotations.

BMC bioinformatics
BACKGROUND: Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones pro...

Computationally predicting protein-RNA interactions using only positive and unlabeled examples.

Journal of bioinformatics and computational biology
Protein-RNA interactions (PRIs) are considerably important in a wide variety of cellular processes, ranging from transcriptional and post-transcriptional regulations of gene expression to the active defense of host against virus. With the development...

PoseR: a deep learning toolbox for classifying animal behaviour.

Open biology
The actions of animals provide a window into how their minds work. Recent advances in deep learning are providing powerful approaches to recognize patterns of animal movement from video recordings using markerless pose estimation models. Current meth...

ReSCU-Nets: Recurrent U-Nets for segmentation of three-dimensional microscopy data.

The Journal of cell biology
Segmenting multidimensional microscopy data requires high accuracy across many images (e.g., time points or Z slices) and is thus a labor-intensive part of biological image processing pipelines. We present ReSCU-Nets, recurrent convolutional neural n...

A deep learning model for accurate segmentation of the Drosophila melanogaster brain from Micro-CT imaging.

Developmental biology
The use of microcomputed tomography (Micro-CT) for imaging biological samples has burgeoned in the past decade, due to increased access to scanning platforms, ease of operation, and the advance of software platforms that enable accurate microstructur...

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 ...

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...