AIMC Topic: Zebrafish

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nanite: using machine learning to assess the quality of atomic force microscopy-enabled nano-indentation data.

BMC bioinformatics
BACKGROUND: Atomic force microscopy (AFM) allows the mechanical characterization of single cells and live tissue by quantifying force-distance (FD) data in nano-indentation experiments. One of the main problems when dealing with biological tissue is ...

Convolutional neural networks for reconstruction of undersampled optical projection tomography data applied to in vivo imaging of zebrafish.

Journal of biophotonics
Optical projection tomography (OPT) is a 3D mesoscopic imaging modality that can utilize absorption or fluorescence contrast. 3D images can be rapidly reconstructed from tomographic data sets sampled with sufficient numbers of projection angles using...

Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio.

PloS one
Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed g...

Convergent Temperature Representations in Artificial and Biological Neural Networks.

Neuron
Discoveries in biological neural networks (BNNs) shaped artificial neural networks (ANNs) and computational parallels between ANNs and BNNs have recently been discovered. However, it is unclear to what extent discoveries in ANNs can give insight into...

Low-Invasive Cell Injection based on Rotational Microrobot.

Advanced biosystems
The advancement of cell injections has created a need for accurate, efficient, and low-invasive injections. However, the conventional approaches to reduce cell damage during penetration, mainly optimization of micropipette tips and vision-based autom...

Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model.

Computational intelligence and neuroscience
Zebrafish embryo fluorescent vessel analysis, which aims to automatically investigate the pathogenesis of diseases, has attracted much attention in medical imaging. Zebrafish vessel segmentation is a fairly challenging task, which requires distinguis...

Deep learning image recognition enables efficient genome editing in zebrafish by automated injections.

PloS one
One of the most popular techniques in zebrafish research is microinjection. This is a rapid and efficient way to genetically manipulate early developing embryos, and to introduce microbes, chemical compounds, nanoparticles or tracers at larval stages...

DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning.

BMC bioinformatics
BACKGROUND: N6-methyladensine (m6A) is a common and abundant RNA methylation modification found in various species. As a type of post-transcriptional methylation, m6A plays an important role in diverse RNA activities such as alternative splicing, an ...

High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology.

Nature communications
Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherap...

Performance of convolutional neural networks for identification of bacteria in 3D microscopy datasets.

PLoS computational biology
Three-dimensional microscopy is increasingly prevalent in biology due to the development of techniques such as multiphoton, spinning disk confocal, and light sheet fluorescence microscopies. These methods enable unprecedented studies of life at the m...