Science Daily5h
New AI models possible game-changers within protein science and healthcare
Researchers have developed new AI models that can vastly improve accuracy and discovery within protein science. Potentially, the models will assist the medical sciences in overcoming present ...
New AI models enhance protein data analysis for medical research
Researchers have developed new AI models that can vastly improve accuracy and discovery within protein science. The models ...
IEEE19d
Event-Driven Transformer-Based Reinforcement Learning for Trajectory Design and Channel Assignment in Multi-UAV Assisted Communication
Abstract: In the assisted communication system with multiple unmanned aerial vehicle base stations (UAV BSs), it is a challenge to achieve optimized trajectory design and channel assignment in unknown ...
IEEE23d
Mean-Field Aided QMIX: A Scalable and Flexible Q-Learning Approach for Large-Scale Agent Groups
Abstract: Value decomposition methods are effective for multi-agent reinforcement learning (MARL), with QMIX being one of the most advanced. However, it struggles with scalability and flexibility in ...
Frontiers25d
Trends in the research and development of peptide drug conjugates: artificial intelligence aided design
Peptide-drug conjugates (PDCs) represent an emerging class of targeted therapeutic agents that consist of small molecular drugs coupled to multifunctional peptides through cleavable or non-cleavable ...
C&EN25d
Protein–Peptide Docking with ESMFold Language Model
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Designing peptide therapeutics requires precise peptide docking, which remains a ...
C&EN29d
Computational Single-Atom Catalyst Database Empowers the Machine Learning Assisted Design of High-Performance Catalysts
Department of Power Engineering, North China Electric Power University, Baoding, Hebei 071003, China Hebei Key Laboratory of Low Carbon and High-Efficiency Power Generation Technology, North China ...