Results 211 to 220 of about 460,060 (291)
Inference for Deep Neural Network Estimators in Generalized Nonparametric Models. [PDF]
Meng X, Li Y.
europepmc +1 more source
A real‐world model of structured animal product restriction practiced for religious reasons reveals the dynamic adaptability of the human gut microbiome to dietary change and uncovers reductions in diversity and rare taxa loss. Integrated microbiome, metabolomic, and proteomic analyses uncover coordinated taxonomic and molecular shifts and identify ...
Christina Emmanouil +7 more
wiley +1 more source
CBMR: Coordinate-based meta-regression for group and covariate inference. [PDF]
Yu Y +5 more
europepmc +1 more source
De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li +23 more
wiley +1 more source
A practice-oriented guide to statistical inference in linear modeling for non-normal or heteroskedastic error distributions. [PDF]
Rajh-Weber H, Huber SE, Arendasy M.
europepmc +1 more source
A healthy gut barrier shields underlying fibroblasts from luminal shear forces, illustrating that “good fences make good neighbors.” Barrier damage exposes fibroblasts to shear stress, inducing cell death and the emergence of stress‐adapted, profibrotic fibroblasts. Sustained shear exposure promotes the formation of stiff aggregates of mechanoadapative
Soyoun Min +6 more
wiley +1 more source
How to improve statistical power in a trial with SCA2 patients using natural history data. [PDF]
Tran M +7 more
europepmc +1 more source
This study generates high‐fidelity synthetic longitudinal records for a million‐patient diabetes cohort, successfully replicating clinical predictive performance. However, deeper analysis reveals algorithmic biases and trajectory inconsistencies that escape standard quality metrics. These findings challenge current validation norms, demonstrating why a
Francisco Ortuño +5 more
wiley +1 more source
Inference of Genetic Networks from Pseudo Time Series of Single-cell Gene Expression Data using Modified Random Forests. [PDF]
Kimura S +4 more
europepmc +1 more source

