Results 221 to 230 of about 252,506 (348)
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu +8 more
wiley +1 more source
Viral lineage and mode of exposure modulate within-host spatial dynamics of influenza A viruses in a guinea pig model. [PDF]
Leyson CM +10 more
europepmc +1 more source
Transposase‐Assisted Donor Tethering Boosts Large‐Fragment HDR in Plants
A transposase‐assisted donor tethering strategy is developed to enhance homology‐directed repair in plants. By recruiting donor DNA to double‐strand breaks and synergizing with repair pathway reprogramming and transcription‐coupled donor design, this system markedly improves large‐fragment targeted insertion efficiency, providing a robust platform for ...
Sha Wei +8 more
wiley +1 more source
Neural barcoding representing cortical spatiotemporal dynamics based on continuous-time Markov chains. [PDF]
Culp JM +5 more
europepmc +1 more source
Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen +6 more
wiley +1 more source
Evaluating SSR marker transferability and plastid barcode variation in native <i>Populus</i> and <i>Salix</i> species of Türkiye. [PDF]
Özdemir Değirmenci F.
europepmc +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source

