Results 221 to 230 of about 2,019,981 (302)

CausalCellInfer: Prioritizing Cell‐Type‐Specific Disease Associations From Genetically Predicted Transcriptomes in Biobank Cohorts

open access: yesAdvanced Science, EarlyView.
Bulk and genotype‐imputed transcriptomes obscure the cellular drivers of complex disease. CausalCellInfer resolves them by integrating invariant marker selection, deep learning deconvolution, and regularized matrix completion. Applied to ∼500 000 UK Biobank participants across 29 traits, it uncovers hallmark cell‐type proportion shifts, including ...
Liangying Yin   +6 more
wiley   +1 more source

Data‐Driven Design of Biofunctional Molecularly Imprinted Polymers for Precision Diagnostics

open access: yesAdvanced Science, EarlyView.
Integrating molecular mechanics/dynamics (MM/MD) with machine learning (ML) enables data‐driven design of nanoMIPs with exceptional performance in multiplex cancer biomarker detection. Guided by the epitopes’ physicochemical and structural traits, ML‐optimized nanoMIPs enhance their charge complementarity, colloidal stability, and binding specificity ...
Nastasia Sanda Moldovean‐Cioroianu   +4 more
wiley   +1 more source

Accelerated Discovery of Earth‐Abundant Oxygen Evolution Catalysts Through Surface‐Informed Active Learning

open access: yesAdvanced Science, EarlyView.
A surface‐informed active learning framework integrated with density functional theory enables resource efficient screening of the NiCoFe ternary composition space. Experimental validation identifies Ni55Co10Fe35 as the optimal composition, exhibiting favorable oxygen evolution reaction kinetics.
Hayun Jeon   +5 more
wiley   +1 more source

Probe‐Free, Primer‐Programmed Amplicon Encoding Enables Nanopore‐Based Multiplex Detection With Deep Learning Decoding

open access: yesAdvanced Science, EarlyView.
Primer‐programmed amplicon encoding enables reporter‐probe‐free multiplex nucleic acid identification using glass nanopore sensing and deep neural network decoding. ABSTRACT Single‐reaction multiplex nucleic acid testing (NATs) must both co‐amplify multiple targets and distinguish the resulting amplicons within the product mixture.
Md. Ahasan Ahamed   +4 more
wiley   +1 more source

XChrom: A Cross‐Cell Chromatin Accessibility Prediction Model Integrating Genomic Sequence and Cellular Context

open access: yesAdvanced Science, EarlyView.
XChrom is a deep learning framework that integrates genomic sequence and single‐cell context to predict chromatin accessibility. It generalizes to unseen cells and genomic regions, enabling cross‐sample and cross‐species analysis. Applied to COVID‐19 patient data, XChrom reveals key transcriptional regulatory mechanisms and disease‐associated ...
Yuanyuan Miao   +5 more
wiley   +1 more source

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