AIMC Topic: Animals

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A machine learning computational approach for the mathematical anthrax disease system in animals.

PloS one
OBJECTIVES: The current research investigations present the numerical solutions of the anthrax disease system in animals by designing a machine learning stochastic procedure. The mathematical anthrax disease system in animals is classified into susce...

Explainable classification of goat vocalizations using convolutional neural networks.

PloS one
Efficient precision livestock farming relies on having timely access to data and information that accurately describes both the animals and their surrounding environment. This paper advances classification of goat vocalizations leveraging a publicly ...

Safety Evaluation of Serendipity Berry Sweet Protein From Komagataella phaffii.

Journal of applied toxicology : JAT
Serendipity Berry Sweet Protein (sweelin) is a novel hyper-sweet thermophilic protein designed using Artificial Intelligence Computational Protein Design (AI-CPD) to improve the stability and sensory profile of the protein found in serendipity berry ...

[Research progress of effect mechanism of acupotomy for knee osteoarthritis].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
Acupotomy therapy demonstrates the definite clinical efficacy on knee osteoarthritis (KOA). After reviewing systematically the mechanism studies on acupotomy for KOA over the past 5 years, It is revealed that acupotomy synergistically intervenes in t...

Scaling Up Synthetic Cell Production Using Robotics and Machine Learning Toward Therapeutic Applications.

Advanced biology
Synthetic cells (SCs), developed through bottom-up synthetic biology, hold great potential for biomedical applications, with the promise of replacing malfunctioning natural cells and treating diseases with spatiotemporal control. Currently, most SC s...

Causal machine learning for single-cell genomics.

Nature genetics
Advances in single-cell '-omics' allow unprecedented insights into the transcriptional profiles of individual cells and, when combined with large-scale perturbation screens, enable measuring of the effect of targeted perturbations on the whole transc...

The reality of modeling irritable bowel syndrome: progress and challenges.

Expert opinion on drug discovery
INTRODUCTION: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is often therapeutically challenging. While research has advanced our understanding of IBS pathophysiology, developing precise models to predict drug response and...

Integration of epigenomic and genomic data to predict residual feed intake and the feed conversion ratio in dairy sheep via machine learning algorithms.

BMC genomics
BACKGROUND: Feed efficiency (FE) is an essential trait in livestock species because of the constant demand to increase the productivity and sustainability of livestock production systems. A better understanding of the biological mechanisms associated...

Advances in AI-based strategies and tools to facilitate natural product and drug development.

Critical reviews in biotechnology
Natural products and their derivatives have been important for treating diseases in humans, animals, and plants. However, discovering new structures from natural sources is still challenging. In recent years, artificial intelligence (AI) has greatly ...

Ultrastructural Morphometry of Mitochondria: Comparison Between Conventional Operator-Dependent and Artificial Intelligence (AI)-Operated Machine Learning Methods.

Microscopy research and technique
Morphometric analysis of digital images is fundamental to substantiate the visual observations with objective quantitative data suitable for statistical analysis. The recent advances in artificial intelligence (AI) have allowed the development of mac...