Results 241 to 250 of about 497,128 (308)

Retrospective In Silico Analysis of Routine Laboratory Data Supports a Specific Association of Epstein-Barr Virus and Multiple Sclerosis. [PDF]

Eur J Neurol
Rodomonti M, Pache F, Otto C, Schindler P, Eberspächer B, Geran R, Puthenparampil M, Gallo P, Wildemann B, Jarius S, Erdur H, Ruprecht K.   +11 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Antioxidant, Anti-inflammatory, Analgesic, and Antiarthritic Potentialities of Methanolic Extract of Fruit Husk of Nypa fruticans Wurmb, Established by In Silico Analysis. [PDF]

Biomed Res Int
Ripa FA, Adar AP, Bishakha AC, Mustafa N, Tanisha MH, Khair NZ, Sheikh Z, Raj A, Bulbul IJ.   +8 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Niosomal mefloquine and cisplatin in breast cancer: comparative effects on apoptosis and angiogenesis via in vitro and in silico analysis. [PDF]

BMC Cancer
Salari Z, Khosravi A, Riahi A, Molaakbari E, Salarkia E, Keyhani AR, Sohbati S, Mansouri G, Khosravi M, Zarif M, Estabragh MAR.   +10 more
europepmc   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Exploring Deleterious Nonsynonymous SNPs in the <i>ACADM</i> Gene: Insights Into Medium-Chain Acyl-CoA Dehydrogenase Deficiency (MCADD) via In Silico Analysis. [PDF]

Genet Res (Camb)
Iqbal MW, Shahab M, Dabiellil F, Bin Jardan YA, Bourhia M, Sun X, Yuan Q.   +6 more
europepmc   +1 more source

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source