AIMC Topic: Animals

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Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BMC medical genomics
BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN.

Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.

PLoS computational biology
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Comp...

Molecular connectomics: Placing cells into morphological tissue context.

PLoS biology
Here we propose "molecular connectomics" to link molecular and morphological cell features in three dimensions across scales, using machine learning and artificial intelligence to reveal emergent properties of complex biological systems.

A machine learning enhanced EMS mutagenesis probability map for efficient identification of causal mutations in Caenorhabditis elegans.

PLoS genetics
Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remains laborious, hindering their high-throughput application. Here, we reveal a non-uniform mutation rat...

Using machine-learning approaches to investigate the volatile-compound fingerprint of fishy off-flavour from beef with enhanced healthful fatty acids.

Meat science
Machine learning classification approaches were used to discriminate a fishy off-flavour identified in beef with health-enhanced fatty acid profiles. The random forest approach outperformed (P < 0.001; receiver operating characteristic curve: 99.8 %,...

The development of machine learning approaches in two-dimensional NMR data interpretation for metabolomics applications.

Analytical biochemistry
Metabolomics has been widely applied in human diseases and environmental science to study the systematic changes of metabolites over diverse types of stimuli. NMR-based metabolomics has been widely used, but the peak overlap problems in the one-dimen...

A novel open-access artificial-intelligence-driven platform for CNS drug discovery utilizing adult zebrafish.

Journal of neuroscience methods
BACKGROUND: Although zebrafish are increasingly utilized in biomedicine for CNS disease modelling and drug discovery, this generates big data necessitating objective, precise and reproducible analyses. The artificial intelligence (AI) applications ha...

Leveraging artificial intelligence for better translation of fibre-based pharmaceutical systems into real-world benefits.

Pharmaceutical development and technology
The increasing prominence of biologics in the pharmaceutical market requires more advanced delivery systems to deliver these delicate and complex drug molecules for better therapeutic outcomes. Fibre technology has emerged as a promising approach for...

Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model.

Lipids in health and disease
BACKGROUND: Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving metabolic, inflammatory, and fibrogenic processes. Despite its burden, there has been a lack of any approved food-and-drug administration therapy up till ...

Neural network auto-segmentation of serial-block-face scanning electron microscopy images exhibit collagen fibril structural differences with tendon type and health.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
A U-Net machine learning algorithm was adapted to automatically segment tendon collagen fibril cross-sections from serial block face scanning electron microscopy (SBF-SEM) and create three-dimensional (3D) renderings. We compared the performance of r...