AIMC Topic: Caenorhabditis elegans
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MGNDTI: A Drug-Target Interaction Prediction Framework Based on Multimodal Representation Learning and the Gating Mechanism.
Journal of chemical information and modeling
Aug 13, 2024
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 ...
Inference of Essential Genes of the Parasite via Machine Learning.
International journal of molecular sciences
Jun 27, 2024
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...
Prediction of Protein-Protein Interactions Based on Integrating Deep Learning and Feature Fusion.
International journal of molecular sciences
May 27, 2024
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...
Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Mar 20, 2024
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
Mar 8, 2024
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...
Mechanical intelligence simplifies control in terrestrial limbless locomotion.
Science robotics
Dec 20, 2023
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
Dec 5, 2023
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...
DensePPI: A Novel Image-Based Deep Learning Method for Prediction of Protein-Protein Interactions.
IEEE transactions on nanobioscience
Oct 3, 2023
Protein-protein interactions (PPI) are crucial for understanding the behaviour of living organisms and identifying disease associations. This paper proposes DensePPI, a novel deep convolution strategy applied to the 2D image map generated from the in...
Predicting lifespan-extending chemical compounds for with machine learning and biologically interpretable features.
Aging
Jul 13, 2023
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...
The million-molecule challenge: a moonshot project to rapidly advance longevity intervention discovery.
GeroScience
Jul 11, 2023
Targeting aging is the future of twenty-first century preventative medicine. Small molecule interventions that promote healthy longevity are known, but few are well-developed and discovery of novel, robust interventions has stagnated. To accelerate l...
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