AIMC Topic: Animals

Clear Filters Showing 2141 to 2150 of 8866 articles

Exploration of the prediction and generation patterns of heterocyclic aromatic amines in roast beef based on Genetic Algorithm combined with Support Vector Regression.

Food chemistry
Heterocyclic aromatic amines (HAAs) are harmful byproducts in food heating. Therefore, exploring the prediction and generation patterns of HAAs is of great significance. In this study, genetic algorithm (GA) and support vector regression (SVR) are us...

Deep structure-level N-glycan identification using feature-induced structure diagnosis integrated with a deep learning model.

Analytical and bioanalytical chemistry
Being a widely occurring protein post-translational modification, N-glycosylation features unique multi-dimensional structures including sequence and linkage isomers. There have been successful bioinformatics efforts in N-glycan structure identificat...

Tracking perching behavior of cage-free laying hens with deep learning technologies.

Poultry science
Providing perches in cage-free (CF) housing offers significant benefits for laying hens, such as improved leg muscle development, bone health, reduced abdominal fat, and decreased fear and aggression. A precise detection method is essential to ensure...

Fractional whale driving training-based optimization enabled transfer learning for detecting autism spectrum disorder.

Computational biology and chemistry
Autism Spectrum Disorder (ASD) is a neurological illness that degrades communication and interaction among others. Autism can be detected at any stage. Early detection of ASD is important in preventing the communication, interaction and behavioral ou...

Suitability of different machine learning algorithms for the classification of the proportion of grassland-based forages at the herd level using mid-infrared spectral information from routine milk control.

Journal of dairy science
As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation policies surrounding this topic. Individual stipulations by countries and milk producers to market t...

Development of a pig wean-quality score using machine-learning algorithms to characterize and classify groups with high mortality risk under field conditions.

Preventive veterinary medicine
Mortality during the post-weaning phase is a critical indicator of swine production system performance, influenced by a complex interaction of multiple factors of the epidemiological triad. This study leveraged retrospective data from 1723 groups of ...

The role of artificial intelligence in the development of anticancer therapeutics from natural polyphenols: Current advances and future prospects.

Pharmacological research
Natural polyphenols, abundant in the human diet, are derived from a wide variety of sources. Numerous preclinical studies have demonstrated their significant anticancer properties against various malignancies, making them valuable resources for drug ...

Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.

Frontiers in immunology
BACKGROUND: Intracerebral hemorrhage (ICH) is a severe stroke subtype with high morbidity, disability, and mortality rates. Currently, no biomarkers for ICH are available for use in clinical practice. We aimed to explore the roles of RNAs in ICH path...

The path to the G protein-coupled receptor structural landscape: Major milestones and future directions.

British journal of pharmacology
G protein-coupled receptors (GPCRs) play a crucial role in cell function by transducing signals from the extracellular environment to the inside of the cell. They mediate the effects of various stimuli, including hormones, neurotransmitters, ions, ph...