Results 211 to 220 of about 142,210 (310)
Neural posterior estimation on exponential random graph models: evaluating bias and implementation challenges. [PDF]
Fan Y, White SR.
europepmc +1 more source
Autoregressive Conditional Density Estimation.
R. F. Engle's autoregressive conditional heteroskedastic model is extended to permit parametric specifications for conditional dependence beyond the mean and variance.
Hansen, Bruce E
core
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 +5 more
wiley +1 more source
Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng +7 more
wiley +1 more source
Observer-Based Source Localization in Tree Infection Networks via Laplace Transforms. [PDF]
O'Connor GK +3 more
europepmc +1 more source
Tumor‐derived lactate activates PSCs through MCT1‐mediated Vps34 lactylation and autophagy. These activated PSCs secrete CXCL9/10, upregulating PD‐1 on CD8+ T cells via the CXCR3/STAT3 axis to foster immunosuppression. Disrupting this metabolic crosstalk by targeting MCT1 effectively sensitizes pancreatic cancer to PD‐1 blockade, presenting a promising
Wenfeng Zhuo +14 more
wiley +1 more source
External factors show reproducible local symptom-biomarker associations in middle-aged and older adults with heart disease. [PDF]
Shi H +10 more
europepmc +1 more source
On Convergent Diffusions: The Densities and the Conditioned Processes [PDF]
openaire +2 more sources
AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi +4 more
wiley +1 more source
What Are We Estimating? Revisiting Standard Nutritional Models Through the Target Trial Framework. [PDF]
Chiu YH, Wen L.
europepmc +1 more source

