Results 141 to 150 of about 48,760 (297)

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

Knowledge graph applications for identifying resilient forage systems

Agricultural & Environmental Letters
Knowledge Graphs organize and connect disparate data for integrating information in a user‐friendly interface for recommendations and applications. This analytical tool for supporting data interrogation has not been widely applied in agronomy.
Amanda J. Ashworth, Alicia Tyson, Timothy Propst, Logan Marshall, Chengkai Li, Jeff J. Volenec, Marisol T. Berti, Valentin Picasso, Jamie L. Foster, Jianzhong Su   +9 more
doaj   +1 more source

DynaKG: Dynamic Knowledge Graph Attention With Learnable Temporal Decay for Recommendation

IEEE Access
Knowledge graph-based recommendation systems excel at capturing semantic relationships but struggle to model temporal dynamics in evolving user preferences, which is a critical limitation for real-world applications where user behaviors and item ...
Bwalya Chomba, Patrick Mukala, Nicanor Mayumu, Saif Ur Rehman Khan   +3 more
doaj   +1 more source

Imaging‐Guided Live Single‐Cell Lipid Profiling of Leader and Follower Cells During Collective Migration of Triple‐Negative Breast Cancer Cells

Advanced Science, EarlyView.
Integrated single‐cell mass spectrometry reveals distinct lipidomic signatures that differentiate leader and follower phenotypes in migratory breast cancer cells. Phenotype‐specific alterations across various lipid classes, including fatty acids and phosphatidylcholines, underpin functional heterogeneity.
Xiaoyue Huang, Judit González Riera, Mai Nguyen, Jeremy Broekhuis, Sylvia E. Le Dévédec, Ahmed Ali, Thomas Hankemeier   +6 more
wiley   +1 more source

TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs [PDF]

Multi-relational temporal graphs are powerful tools for modeling real-world data, capturing the evolving and interconnected nature of entities over time.
Gastinger, Julia, Rabusseau, Guillaume, Koutis, Ioannis, Danovitch, Jacob, Rossi, Emanuele, Huang, Shenyang, Galkin, Mikhail, Loghmani, Erfan, Parviz, Ali, Poursafaei, Farimah, Rabbany, Reihaneh, Stuckenschmidt, Heiner   +11 more
core  

A Spatio-Temporal Evolutionary Embedding Approach for Geographic Knowledge Graph Question Answering

ISPRS International Journal of Geo-Information
In recent years, geographic knowledge graphs (GeoKGs) have shown great promise in representing spatio-temporal and event-driven knowledge. However, existing knowledge graph embedding approaches mainly focus on structural patterns and often overlook the ...
Chunju Zhang, Chaoqun Chu, Kang Zhou, Shu Wang, Yunqiang Zhu, Jianwei Huang, Zhaofu Wu, Fei Gao   +7 more
doaj   +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

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

Advanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li, Jialuo Xu, Gaoyuan Du, Xiangting Jia, Dongmin Zhao, Chunyan Zhou, Kexin Xiao, Jia Gu, Junnan Zhu, Xuequn Shang   +9 more
wiley   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

Advanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su, Yanda Zhu, Hao Peng, Manman Li, Xuzihan Zhang, Meixiao Wu, Siyuan Zhang, Yuhan Zeng, Jiwen Liao, Ming Luo, Hetaishan Huang, Yutong Wang, Sean Li, Wenxian Li   +13 more
wiley   +1 more source

A dynamic preference recommendation model based on spatiotemporal knowledge graphs

Complex & Intelligent Systems
Recommender systems are of increasing importance owing to the growth of social networks and the complexity of user behavior, and cater to the personalized needs of users.
Xinyu Fan, Yinqin Ji, Bei Hui
doaj   +1 more source