Results 161 to 170 of about 1,235,780 (284)

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

Advanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio, Tommaso Gili, Andrea Gabrielli, Maurizio Mattia   +3 more
wiley   +1 more source

Identification and validation of qPC-3A, a stable QTL for flour protein content in hard wheat (Triticum aestivum L.). [PDF]

Theor Appl Genet
Cha JK, Park H, Jang SG, Kwon Y, Lee SM, Kim KM, Kim WJ, Lee JH.   +7 more
europepmc   +1 more source

Diversity Patterns of Domestic Herbivore Viruses in China Reveal Transmission Dynamics with Disease Management Implications

Advanced Science, EarlyView.
This study performs pan‐viromic profiling of 14,529 samples from 5,710 domestic herbivores across five Chinese provinces, establishing the DhCN‐Virome (1,085,360 viral metagenomes). It reveals species/sample‐specific viromic signatures and cross‐species transmission dynamics, aiding unified disease control.
Yue Sun, Yong Li, Bagen Temur, Yuanqing Lin, Yuhang Liu, Le Yi, Zheng Sun, Gang Zhang, Jun Li, Yu Guo, Linchuan Li, Jinshan Cai, Wenliang Tian, Gen Meng, Lingling Jiang, Min Fang, Fuying Ding, Xuezhang Zhou, Changchun Tu, Biao He   +19 more
wiley   +1 more source

Kernel-DMD for multiome data integration and control. [PDF]

PLoS Comput Biol
Pierides I, Kramml HM, Waldherr S, Weckwerth W.   +3 more
europepmc   +1 more source

SKOOTS: Skeleton‐Oriented Object Segmentation for Mitochondria in High‐Resolution Cochlear EM Datasets

Advanced Science, EarlyView.
Skeleton‐oriented object segmentation (SKOOTS) introduces a new strategy for 3D mitochondrial instance segmentation by predicting explicit skeletons rather than relying on boundary cues. This approach enables robust analysis of densely packed organelles in large FIB‐SEM datasets.
Christopher J. Buswinka, Richard T. Osgood, Hidetomi Nitta, Artur A. Indzhykulian   +3 more
wiley   +1 more source

Assessing the influence of kernel selection on chest computed tomography image quality across varying dose levels using TrueFidelity reconstruction. [PDF]

Radiat Prot Dosimetry
Gianko E, Oliveira Diniz M, Cifuentes Ramirez W, Rossi Norrlund R, Johnsson ÅA, Båth M, Svalkvist A.   +6 more
europepmc   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

Identification of transcription factors regulating starch biosynthesis in maize through integrated GWAS and transcriptomic analysis. [PDF]

BMC Plant Biol
Han J, Li R, Liu Q, Zhang Z, Li G, Xu Z, Zhou Z, Weng J, Hao Z, Zhang D, Yong H, Li X, Li M.   +12 more
europepmc   +1 more source

Learnable Diffusion Framework for Mouse V1 Neural Decoding

Advanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng, Peter S. Schwendeman, Yuanfang Guan   +2 more
wiley   +1 more source

SGA-DT: An adaptive fusion framework for missing data imputation and interpretable healthcare classification. [PDF]

PLoS One
Jena M, Dehuri S, Cho SB.
europepmc   +1 more source