AIMC Topic: Animals

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Predicting adaptive immune receptor specificities by machine learning is a data generation problem.

Cell systems
Determining the specificity of adaptive immune receptors-B cell receptors (BCRs), their secreted form antibodies, and T cell receptors (TCRs)-is critical for understanding immune responses and advancing immunotherapy and drug discovery. Immune recept...

Reading the repertoire: Progress in adaptive immune receptor analysis using machine learning.

Cell systems
The adaptive immune system holds invaluable information on past and present immune responses in the form of B and T cell receptor sequences, but we are limited in our ability to decode this information. Machine learning approaches are under active in...

How to build the virtual cell with artificial intelligence: Priorities and opportunities.

Cell
Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a mult...

[Preliminary experiment on simulated human manual acupuncture of intelligent acupuncture robot based on miniature pigs].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
OBJECTIVE: To evaluate the performance of a newly developed intelligent acupuncture robot that simulates human manual acupuncture techniques through an animal experiment using miniature pigs.

Characterization of double-stranded RNA and its silencing efficiency for insects using hybrid deep-learning framework.

Briefings in functional genomics
RNA interference (RNAi) technology is widely used in the biological prevention and control of terrestrial insects. One of the main factors with the application of RNAi in insects is the difference in RNAi efficiency, which may vary not only in differ...

Identification of Ferroptosis-Related Gene in Age-Related Macular Degeneration Using Machine Learning.

Immunity, inflammation and disease
BACKGROUND: Age-related macular degeneration (AMD) is a major cause of irreversible visual impairment, with dry AMD being the most prevalent form. Programmed cell death of retinal pigment epithelium (RPE) cells is a central mechanism in the pathogene...

AI: A transformative opportunity in cell biology.

Molecular biology of the cell
The success of artificial intelligence (AI) algorithms in predicting protein structure and more recently, protein interactions, demonstrates the power and potential of machine learning and AI for advancing and accelerating biomedical research. As cel...

Quantification of Empty Lacunae in Tissue Sections of Osteonecrosis of the Femoral Head Using YOLOv8 Artificial Intelligence Model.

Journal of biomedical materials research. Part B, Applied biomaterials
Histomorphometry is an important technique in the evaluation of non-traumatic osteonecrosis of the femoral head (ONFH). Quantification of empty lacunae and pyknotic cells on histological images is the most reliable measure of ONFH pathology, yet it i...

Identification of KCNQ1 as a diagnostic biomarker related to endoplasmic reticulum stress for intervertebral disc degeneration based on machine learning and experimental evidence.

Medicine
Intervertebral disc degeneration (IDD) is a primary cause of low back pain and disability. Cellular senescence and apoptosis due to endoplasmic reticulum stress (ERS) are key in IDD pathology. Identifying biomarkers linked to ERS in IDD is crucial fo...

Tiberius: end-to-end deep learning with an HMM for gene prediction.

Bioinformatics (Oxford, England)
MOTIVATION: For more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al. demonstrated with their program Helixer that the accuracy of...