AIMC Topic: Animals

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Machine learning for genomic prediction of growth traits in aquaculture: a case study of the Australasian snapper (Chrysophrys auratus).

BMC bioinformatics
BACKGROUND: Chrysophrys auratus (family: Sparidae), commonly known as Australasian snapper, is a warm-water species being developed as a candidate for aquaculture in New Zealand. Genomic selection of elite snapper offers significant potential to acce...

A Machine Learning-Empowered Quantitative Structure-Activity Relationship Model for Predicting the Plasma Half-life of Drugs in Dogs.

The AAPS journal
Understanding a drug's plasma half-life is essential in guiding dosage regimens and optimizing therapeutic outcomes, particularly in the early stages of drug development. By using published pharmacokinetic data from Food Animal Residue Avoidance Data...

Differences in acoustic presence and vocal behavior of Spitsbergen's bowhead whales under ice-covered and open-water conditions.

Scientific reports
Arctic-endemic bowhead whales (Balaena mysticetus) are facing extreme habitat changes, particularly due to ongoing sea-ice loss. This study compares acoustic presence and vocal behavior of bowhead whales at two ecologically distinct locations: (1) no...

Towards scalable age-grading of Aedes albopictus mosquito using mid-infrared spectroscopy and machine learning.

Scientific reports
The age structure and dynamics of mosquito populations are crucial for understanding their ability to spread diseases and assessing the effectiveness of anti-mosquito control measures. However, available methods to age-grade mosquito populations are ...

Whistles characterisation using artificial intelligence reveals responses of short-beaked common dolphins to a bio-inspired acoustic mitigation device for fishing nets.

Scientific reports
Understanding cetacean whistles is crucial for assessing their social interactions, behaviours, and responses to anthropic activities. Identifying the various types of whistles present in acoustic recordings is often challenging, but necessary for th...

Explainable multi stream deep learning for fine grained camel breed classification using a Novel Arabian and Non Arabian dataset.

Scientific reports
Camels are resilient animals that play a crucial role in arid ecosystems and desert communities. However, distinguishing between visually similar camel breeds-particularly among Arabian camels-remains a challenging task. This paper introduces a novel...

Stable intracranial imaging of dura mater-engrafted pancreatic islet cells in awake mice.

Nature communications
By transplanting pancreatic islets onto the dura mater of the mouse brain, we establish a microscopy platform that enables longitudinal intravital imaging of otherwise optically inaccessible tissue. The system combines a cranial window with an air-cu...

A deep learning approach for the analysis of birdsong.

eLife
Deep learning tools for behavior analysis have enabled important insights and discoveries in neuroscience. Yet, they often compromise interpretability and generalizability for performance, making quantitative comparisons across datasets difficult. We...

Transforming microfluidics for single-cell analysis with robotics and artificial intelligence.

Lab on a chip
Single-cell analysis has advanced biomedical research by revealing cellular heterogeneity with unprecedented resolution, identifying rare subpopulations that drive disease progression and therapeutic resistance. Microfluidics is central to this advan...

FormulationLAI: A physiology-based machine learning framework for accelerated development of long-acting injectable formulations.

Journal of controlled release : official journal of the Controlled Release Society
Long-acting injectables (LAIs) represent promising drug delivery platforms for chronic diseases management, but their clinical translation remains constrained by extremely long trial-and-error experiments (8-10 years), limited mechanism insights, and...