AIMC Topic: Animals

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Robust mouse tracking in complex environments using neural networks.

Communications biology
The ability to track animals accurately is critical for behavioral experiments. For video-based assays, this is often accomplished by manipulating environmental conditions to increase contrast between the animal and the background in order to achieve...

Comparison between random forest and gradient boosting machine methods for predicting Listeria spp. prevalence in the environment of pastured poultry farms.

Food research international (Ottawa, Ont.)
Foodborne pathogens such as Listeria spp. contain the ability to survive and multiply in poultry farming environments, which provides a route of contamination for poultry processing environments and final poultry products. An understanding of the eff...

Dissecting the Catecholamines: How New Approaches Will Facilitate the Distinction between Noradrenergic and Dopaminergic Systems.

ACS chemical neuroscience
To overcome the limitations of fast scan cyclic voltammetry (FSCV) to discriminate between catecholamines, we discuss new approaches to monitor the dynamics of these neurochemicals with high spatial, genetic, and temporal specificity.

Comparison between two programs for image analysis, machine learning and subsequent classification.

Tissue & cell
In the early 1950s, flow cytometry was developed as the first method for automated quantitative cellular analysis. In the early 1990s, the first equipment for image cytometry (laser scanning cytometry, LSC) became commercially available. As flow cyto...

Deep Collaborative Filtering for Prediction of Disease Genes.

IEEE/ACM transactions on computational biology and bioinformatics
Accurate prioritization of potential disease genes is a fundamental challenge in biomedical research. Various algorithms have been developed to solve such problems. Inductive Matrix Completion (IMC) is one of the most reliable models for its well-est...

Latent Phase Detection of Hypoxic-Ischemic Spike Transients in the EEG of Preterm Fetal Sheep Using Reverse Biorthogonal Wavelets & Fuzzy Classifier.

International journal of neural systems
Hypoxic-ischemic (HI) studies in preterms lack reliable prognostic biomarkers for diagnostic tests of HI encephalopathy (HIE). Our group's observations from fetal sheep models suggest that potential biomarkers of HIE in the form of developing HI mic...

Smeared multiscale finite element model for electrophysiology and ionic transport in biological tissue.

Computers in biology and medicine
Basic functions of living organisms are governed by the nervous system through bidirectional signals transmitted from the brain to neural networks. These signals are similar to electrical waves. In electrophysiology the goal is to study the electrica...

Mass Surveilance of -Smartphone-Based DIY Microscope and Machine-Learning-Based Approach for Worm Detection.

Sensors (Basel, Switzerland)
The nematode is often used as an alternative animal model due to several advantages such as morphological changes that can be seen directly under a microscope. Limitations of the model include the usage of expensive and cumbersome microscopes, and r...

NeuroPIpred: a tool to predict, design and scan insect neuropeptides.

Scientific reports
Insect neuropeptides and their associated receptors have been one of the potential targets for the pest control. The present study describes in silico models developed using natural and modified insect neuropeptides for predicting and designing new n...

Deep learning for high-throughput quantification of oligodendrocyte ensheathment at single-cell resolution.

Communications biology
High-throughput quantification of oligodendrocyte myelination is a challenge that, if addressed, would facilitate the development of therapeutics to promote myelin protection and repair. Here, we established a high-throughput method to assess oligode...