Results 101 to 110 of about 56,025 (214)
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Bistable Networks Enable Complex Shape Changes
Transition‐controlled metamaterials are networks of bistable mechanical memory that store local binary states and express them as global shape change. By decoupling low‐force programming from high‐force holding, a single lattice is reconfigured into distinct 2D profiles and 3D surfaces without continuous actuation, enabling reusable morphing materials ...
Sawyer Thomas, Jeffrey Lipton
wiley +1 more source
Using a minimal set of experimentally labeled antimicrobial and non‐antimicrobial peptides, we reconstruct the effective lipid composition of a pathogenic membrane ‐demonstrated at the example of bacterial membranes‐ through a physics‐based evolutionary molecular dynamics (Evo‐MD) approach. Optimization based on peptide insertion reveals broad‐spectrum
Maximilian Krebs, Herre Jelger Risselada
wiley +1 more source
FES‐derived MGE spheroids exhibit progenitor‐stage alterations in developmental trajectory and hypoxia‐responsive transcriptional programs, followed by functional disruption. Gestational hypoxia recapitulates impaired progenitor proliferation, shortened cell‐cycle progression, interneuron developmental abnormalities, and schizophrenia‐like behaviors in
Peiyan Ni +17 more
wiley +1 more source
The iLEAP technique integrates high‐throughput two‐photon lithography with extrusion printing, bridging sub‐micrometer precision and macroscopic scaffold fabrication. By employing a low‐exothermic photoinitiator, it mitigates thermal damage to biopolymers and preserves bioactivity.
Qifeng Guan +11 more
wiley +1 more source
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi +7 more
wiley +1 more source
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao +6 more
wiley +1 more source
Vision begins not with images but with change: the retina fires only when something moves, handing the brain a stream of spikes. A neuromorphic imaging system adopts the same strategy—an event sensor that sees like the retina, a spiking network that thinks like the brain—to track and reconstruct fully randomly moving targets through tissue (phantom ...
Ning Zhang, Arto Nurmikko
wiley +1 more source
Neuromorphic Devices and Computing for Sensing, Memory, and Control
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu +2 more
wiley +1 more source
Inverse Design of Pre‐Strain via a Predictive Electromechanical Model for Enhanced Strain Sensing
An analytical electromechanical model rooted in microcrack evolution mechanics is globally calibrated from only eight pre‐strain datasets, enabling prediction of the complete sensing response at untested pre‐strain values within the calibrated design space (R2 > 0.99).
Jia‐Chen Shang +10 more
wiley +1 more source

