Results 81 to 90 of about 66,359 (302)

Artificial Intelligence‐Based Body Composition Analysis Reveals Sex‐Specific Prognostic Markers and Their Clinical Value in Gastric Cancer: A Multicenter Study

Advanced Science, EarlyView.
This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li, Tingting Liu, Qian Yang, Zhiqing Zhang, Xiaofang Guo, Xiang Wang, Yihan Zhang, Limin Ge, Yu Su, Wenjun Wu, Weihua Guo, Zheng Wang, Lian Yang, Yanfeng Niu   +13 more
wiley   +1 more source

AI‐Designed Cyclic Peptides Enable Controllable Modulation of the CD28 Immune Checkpoint

Advanced Science, EarlyView.
AI‐designed cyclic peptides enable controllable modulation of the CD28 immune checkpoint through reversible disruption of CD28‐CD80/CD86 interactions. The lead peptide, CIP‐3, suppresses T‐cell activation without intrinsic agonist activity, demonstrates dose‐dependent efficacy in a murine colitis model, and attenuates inflammatory cytokine production ...
Katarzyna Kuncewicz, Saurabh Upadhyay, Renjie Zhu, Hongliang Duan, Moustafa T. Gabr   +4 more
wiley   +1 more source

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

FedDrip: Federated Learning With Diffusion-Generated Synthetic Image

IEEE Access
In the realm of machine learning in healthcare, federated learning (FL) is often recognized as a practical solution for addressing issues related to data privacy and data distribution.
Karin Huangsuwan, Timothy Liu, Simon See, Aik Beng Ng, Peerapon Vateekul   +4 more
doaj   +1 more source

Quantum simulation of CO2 chemisorption in an amine-functionalized metal–organic framework [PDF]

AIP Advances
We perform a series of calculations using simulated quantum processing units (QPUs), accelerated by the NVIDIA CUDA-Q platform, focusing on a molecular analog of an amine-functionalized metal–organic framework, a promising class of materials for CO2 ...
Jonathan R. Owens, Marwa H. Farag, Pooja Rao, Annarita Giani   +3 more
doaj   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search

BMC Bioinformatics
Background The maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive.
Bertil Schmidt, Felix Kallenborn, Alejandro Chacon, Christian Hundt   +3 more
doaj   +1 more source

Solar Irradiance Forecasting Using a Hybrid Quantum Neural Network: A Comparison on GPU-Based Workflow Development Platforms

IEEE Access
Modern renewable power operations can be enhanced by integrating deep neural networks, particularly for forecasting solar irradiance. Recent advancements in quantum computing have shown potential improvements in classical deep neural networks.
Ying-Yi Hong, Dylan Josh Domingo Lopez, Yun-Yuan Wang   +2 more
doaj   +1 more source

2021년 KISTI-NVIDIA GPU 해커톤 개최 [PDF]

, 2022
한국과학기술정보연구원(원장 김재수, 이하 KISTI)은 엔비디아(CEO 젠슨 황, 이하 NVIDIA), OpenACC와 함께 2021년‘KISTI-NVIDIA GPU Hackathon’을 8월 25일부터 9월 1일까지 온라인으로 개최했다. 올해로 2회째를 맞는 이번 해커톤에는 대학·기업·기관 등 총 6개 팀이 참가하였으며, KISTI의 슈퍼컴퓨터 보조시스템인 GPU 클러스터(NEURON)를 활용하여 AI 연구개발, HPC 코드 가속화 등의 프로젝트를
한국과학기술정보연구원
core  

Lessons From Drug Discovery for Cryoprotective Agent Design: An AI‐Oriented Perspective

Advanced Science, EarlyView.
Cryoprotectant design is reframed through the lens of drug discovery as a multiparameter optimization problem. This perspective highlights how AI and systematic design strategies could enable safer, more effective cryoprotectants, while identifying key limitations that currently constrain predictive progress in cryobiology. ABSTRACT Cryopreservation is
Dominika Wilczok, Jesús Valdés‐Hernández, Varinia Bernales, Alán Aspuru‐Guzik, Alex Zhavoronkov   +4 more
wiley   +1 more source