AIMC Topic: Animals

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BioKA: a curated and integrated biomarker knowledgebase for animals.

Nucleic acids research
Biomarkers play an important role in various area such as personalized medicine, drug development, clinical care, and molecule breeding. However, existing animals' biomarker resources predominantly focus on human diseases, leaving a significant gap i...

Approaches for predicting dairy cattle methane emissions: from traditional methods to machine learning.

Journal of animal science
Measuring dairy cattle methane (CH4) emissions using traditional recording technologies is complicated and expensive. Prediction models, which estimate CH4 emissions based on proxy information, provide an accessible alternative. This review covers th...

Modeling energy partition patterns of growing pigs fed diets with different net energy levels based on machine learning.

Journal of animal science
The objectives of this study were to evaluate the energy partition patterns of growing pigs fed diets with different net energy (NE) levels based on machine learning methods, and to develop prediction models for the NE requirement of growing pigs. Tw...

Integration of transcriptome and machine learning to identify the potential key genes and regulatory networks affecting drip loss in pork.

Journal of animal science
Low level of drip loss (DL) is an important quality characteristic of meat with high economic value. However, the key genes and regulatory networks contributing to DL in pork remain largely unknown. To accurately identify the key genes affecting DL i...

Using deep learning to accurately detect sow vulva size in a group pen with a single camera.

Journal of animal science
This paper presents a non-contact method for the detection of changes in sow vulva size in a group pen. The traditional approach to estrus detection is manually pressing down on the back of the sow to elicit standing responses; however, this method c...

Discovering genotype-phenotype relationships with machine learning and the Visual Physiology Opsin Database (VPOD).

GigaScience
BACKGROUND: Predicting phenotypes from genetic variation is foundational for fields as diverse as bioengineering and global change biology, highlighting the importance of efficient methods to predict gene functions. Linking genetic changes to phenoty...

spatiAlign: an unsupervised contrastive learning model for data integration of spatially resolved transcriptomics.

GigaScience
BACKGROUND: Integrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly wh...

E-validation - Unleashing AI for validation.

ALTEX
The validation of new approach methods (NAMs) in toxicology faces significant challenges, including the integration of diverse data, selection of appropriate reference chemicals, and lengthy, resource-intensive consensus processes. This article propo...

Path planning optimization for swine manure-cleaning robots through enhanced slime mold algorithm with cellular automata.

Animal science journal = Nihon chikusan Gakkaiho
One of the primary challenges for robotic manure cleaners in pig farming is to plan the shortest path to designated cleaning points under specified conditions with minimal processing cost and time, while avoiding collisions. However, pigs are randoml...

DNeuroMAT: A Deep-Learning-Based Neuron Morphology Analysis Toolbox.

Methods in molecular biology (Clifton, N.J.)
Digital reconstruction of neuronal structures from 3D neuron microscopy images is critical for the quantitative investigation of brain circuits and functions. Currently, neuron reconstructions are mainly obtained by manual or semiautomatic methods. H...