Results 51 to 60 of about 128 (127)
Multiphoton Quantum Reservoirs For Robust Multidimensional Computing
Projective measurements reveal hidden multidimensional quantum networks within classical multiphoton fields, enabling robust quantum reservoirs for room‐temperature quantum simulation, prediction, and information processing. These networks transform noisy classical photonic platforms into scalable quantum computational architectures.
Mingyuan Hong +10 more
wiley +1 more source
MolDBG is a site‐aware, sequence‐only framework that unifies drug‐target affinity prediction, binding‐site identification, and affinity‐conditioned molecular generation for structured proteins. Guided by multi‐task binding‐site supervision, it aligns interaction‐critical residues before learning drug‐target representations and simultaneously infers ...
Gang Luo +6 more
wiley +1 more source
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang +9 more
wiley +1 more source
A multimodal fusion framework integrating sequence, atomic, and fragment representations captures drug–target interactions across multiple scales. The model delivers strong predictive performance and enables efficient virtual screening. Applied to hematopoietic progenitor kinase 1 (HPK1), it identifies structurally diverse inhibitors with nanomolar ...
Shuo Liu +7 more
wiley +1 more source
A Reconfigurable Memristive Spiking Neuron Enabling Advanced Neuromorphic Computing
Pek Jun Tiw and co‐workers develop a reconfigurable memristive neuron that can exhibit four spiking behaviors with freely tunable spike train parameters. The neuron supports multiplexed spike encoding of multiple pieces of information. It also supports advanced neural network strategies, such as neural heterogeneity and dynamic mode switching ...
Pek Jun Tiw +6 more
wiley +1 more source
Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis
Robotic experimentation and physics‐informed machine learning combine to predict enzyme substrate scope. With a handful of interpretable features derived from docking and quantum mechanics calculations, our model rivals descriptor‐heavy AI approaches and extrapolates to unseen substrates and enzyme classes.
Natalia Onishchenko +8 more
wiley +1 more source
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
CDegSR, a new tool for imaging RNA at single molecule level in living cells was developed by researchers. Background noise was eliminated by protein engineering and making it degrade when not bound to its target. This allowed individual RNA molecules to be clearly imaged and tracked.
Shipeng Shao, Hongchen Zhang
wiley +1 more source
Recent advances in metasurface‐enabled low‐observable technologies are reviewed from the perspective of cross‐scale material–structure synergy. Electromagnetic, thermal, optical, and acoustic stealth are highlighted together with dynamic tuning, programmable coding, data‐driven inverse design, artificial intelligence, multispectral compatibility, and ...
Shuhao Wang +5 more
wiley +1 more source
MAPA transforms complex multi‐omics data into biologically coherent functional modules by integrating pathway information with molecular interaction networks. Retrieval‐augmented large language models then generate structured, literature‐informed interpretations.
Yifei Ge +13 more
wiley +1 more source

