Results 271 to 280 of about 7,343,069 (347)

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

open access: yesAdvanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu   +8 more
wiley   +1 more source

Hybrid Digital Twin Framework for Personalized Diabetes Management Using Mathematical Modelling and Machine Learning. [PDF]

open access: yesDiagnostics (Basel)
Dennish V   +6 more
europepmc   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

open access: yesAdvanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia   +4 more
wiley   +1 more source

MXene‐Based Room‐Temperature NO2 Gas Sensors: A Meta‐Analysis

open access: yesAdvanced Science, EarlyView.
This study presents the first comprehensive meta‐analysis of MXene‐based NO2 sensors, decoding 32 study characteristics across 61 peer‐reviewed studies. By isolating materials chemistry as the primary performance driver over device‐level parameters, the authors establish a methodological blueprint and a predictive structure–function map to accelerate ...
Alexander Khort   +3 more
wiley   +1 more source

Integrating clinical and economic outcomes in the elderly myeloma management: a comparative cost-effectiveness analysis. [PDF]

open access: yesFront Oncol
Solimando AG   +11 more
europepmc   +1 more source

Probabilistic Computing via Gate‐Tunable Random Telegraph Noise

open access: yesAdvanced Science, EarlyView.
Intrinsic random telegraph noise in metal–oxide–semiconductor field‐effect transistors is harnessed to create gate‐tunable probabilistic bits. By modulating carrier‐trapping dynamics, the device produces stochastic binary outputs with a continuous bias‐to‐probability transfer.
Gyungwon Yun   +8 more
wiley   +1 more source

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