AIMC Topic: Animals

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Inferring Historical Introgression with Deep Learning.

Systematic biology
Resolving phylogenetic relationships among taxa remains a challenge in the era of big data due to the presence of genetic admixture in a wide range of organisms. Rapidly developing sequencing technologies and statistical tests enable evolutionary rel...

Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies.

Neural computation
Catastrophic forgetting remains an outstanding challenge in continual learning. Recently, methods inspired by the brain, such as continual representation learning and memory replay, have been used to combat catastrophic forgetting. Associative learni...

Combination of deep learning and 2D CARS figures for identification of amyloid-β plaques.

Optics express
In vivo imaging and accurate identification of amyloid-β (Aβ) plaque are crucial in Alzheimer's disease (AD) research. In this work, we propose to combine the coherent anti-Stokes Raman scattering (CARS) microscopy, a powerful detection technology fo...

Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys.

Zoological research
Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction. However, action recognition currently used in non-human primate (NHP) research relies heavily on intense man...

Diagnostic Detection of H7N3 Low Pathogenicity Avian Influenza in a Commercial Game Bird Flock.

Avian diseases
Low pathogenicity avian influenza (LPAI) H7N3 was diagnosed in a flock of commercially raised Japanese quail () breeder hens. The birds were submitted with an initial complaint of a drop in egg production and watery droppings. Initial PCR testing of ...

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward.

Integrative and comparative biology
While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and out...

BEENE: deep learning-based nonlinear embedding improves batch effect estimation.

Bioinformatics (Oxford, England)
MOTIVATION: Analyzing large-scale single-cell transcriptomic datasets generated using different technologies is challenging due to the presence of batch-specific systematic variations known as batch effects. Since biological and technological differe...

Deep-Masker: A Deep Learning-based Tool to Assess Chord Length from Murine Lung Images.

American journal of respiratory cell and molecular biology
Chord length is an indirect measure of alveolar size and a critical endpoint in animal models of chronic obstructive pulmonary disease (COPD). In assessing chord length, the lumens of nonalveolar structures are eliminated from measurement by various ...