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AiGPro: a multi-tasks model for profiling of GPCRs for agonist and antagonist.
J Cheminform
January 2025
School of Systems Biomedical Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, 06978, Seoul, Republic of Korea.
G protein-coupled receptors (GPCRs) play vital roles in various physiological processes, making them attractive drug discovery targets. Meanwhile, deep learning techniques have revolutionized drug discovery by facilitating efficient tools for expediting the identification and optimization of ligands. However, existing models for the GPCRs often focus on single-target or a small subset of GPCRs or employ binary classification, constraining their applicability for high throughput virtual screening.
View Article and Find Full Text PDFA guidance to intelligent metamaterials and metamaterials intelligence.
Nat Commun
January 2025
ZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou, China.
The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the strong nonlinear fitting and generalization ability, artificial intelligence is poised to serve as a materials-savvy surrogate electromagnetic simulator and a high-speed computing nucleus that drives numerous self-driving metamaterial applications, such as invisibility cloak, imaging, detection, and wireless communication. In turn, metamaterials create a versatile electromagnetic manipulator for wave-based analogue computing to be complementary with conventional electronic computing.
View Article and Find Full Text PDFTPepRet: a deep learning model for characterizing T cell receptors-antigen binding patterns.
Bioinformatics
January 2025
School of Computer Science and engineering, Central South University, Changsha, 410083, China.
Motivation: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer immunotherapy, vaccine design, and autoimmune disease management. Understanding the intricate binding patterns between TCRs and peptides is critical for advancing these clinical applications. While several computational tools have been developed, they neglect the directional semantics inherent in sequence data, which are essential for accurately characterizing TCR-peptide interactions.
View Article and Find Full Text PDFOptimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.
Comput Biol Med
January 2025
Department of Medicine (HSRD), Baylor College of Medicine, Houston, TX, USA. Electronic address:
This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require careful anticoagulation management. With rising rates of diabetes and cardiovascular diseases, understanding the factors influencing warfarin therapy is vital for improving patient outcomes and reducing adverse events. Data was sourced from the IWPC dataset, examining characteristics such as age, gender, diabetes status, indication for warfarin, weight, and height.
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