AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Caenorhabditis elegans

Showing 11 to 20 of 92 articles

Clear Filters

Predicting lifespan-extending chemical compounds for with machine learning and biologically interpretable features.

Aging
Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse da...

Expression and Purification of SMGL-1.

Studies in health technology and informatics
Recombinant protein expression is a crucial technique in biology, with E. coli being the most widely used expression system. However, due to growth pressure, the expression of large molecular weight proteins in E. coli has remained a challenging task...

Mechanical intelligence simplifies control in terrestrial limbless locomotion.

Science robotics
Limbless locomotors, from microscopic worms to macroscopic snakes, traverse complex, heterogeneous natural environments typically using undulatory body wave propagation. Theoretical and robophysical models typically emphasize body kinematics and acti...

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation.

Nature methods
Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convoluti...

Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-modifying treatments for PD remains a major unmet medical need. Notably, drug repositioning is becomin...

GraphsformerCPI: Graph Transformer for Compound-Protein Interaction Prediction.

Interdisciplinary sciences, computational life sciences
Accurately predicting compound-protein interactions (CPI) is a critical task in computer-aided drug design. In recent years, the exponential growth of compound activity and biomedical data has highlighted the need for efficient and interpretable pred...

Prediction of Protein-Protein Interactions Based on Integrating Deep Learning and Feature Fusion.

International journal of molecular sciences
Understanding protein-protein interactions (PPIs) helps to identify protein functions and develop other important applications such as drug preparation and protein-disease relationship identification. Deep-learning-based approaches are being intensel...

Inference of Essential Genes of the Parasite via Machine Learning.

International journal of molecular sciences
Over the years, comprehensive explorations of the model organisms (elegant worm) and (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive func...

MGNDTI: A Drug-Target Interaction Prediction Framework Based on Multimodal Representation Learning and the Gating Mechanism.

Journal of chemical information and modeling
Drug-Target Interaction (DTI) prediction facilitates acceleration of drug discovery and promotes drug repositioning. Most existing deep learning-based DTI prediction methods can better extract discriminative features for drugs and proteins, but they ...

Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.

IEEE/ACM transactions on computational biology and bioinformatics
BACKGROUND: Antimicrobial resistance is a major public health threat, and new agents are needed. Computational approaches have been proposed to reduce the cost and time needed for compound screening.