Results 81 to 90 of about 76,758 (254)

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

A statistical framework for detecting mislabeled and contaminated samples using shallow-depth sequence data

BMC Bioinformatics, 2018
Background Researchers typically sequence a given individual multiple times, either re-sequencing the same DNA sample (technical replication) or sequencing different DNA samples collected on the same individual (biological replication) or both.
Ariel W. Chan, Amy L. Williams, Jean-Luc Jannink   +2 more
doaj   +1 more source

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell–Cell Interaction Inference

Advanced Science, EarlyView.
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley   +1 more source

Sparse Grassmannian Design for Noncoherent Codes via Schubert Cell Decomposition

IEEE Open Journal of the Communications Society
In this paper, we propose a method for designing sparse Grassmannian codes for noncoherent multiple-input multiple-output systems. Conventional pairwise error probability formulations under uncorrelated Rayleigh fading channels fail to account for rank ...
Joe Asano, Yuto Hama, Hiroki Iimori, Chandan Pradhan, Szabolcs Malomsoky, Naoki Ishikawa   +5 more
doaj   +1 more source

An exciting Approach to Theoretical Spectroscopy

Advanced Science, EarlyView.
ABSTRACT Theoretical spectroscopy, and more generally, electronic‐structure theory, are powerful concepts for describing the complex many‐body interactions in materials. They cover methods from ground‐state properties to lattice excitations and light‐matter interaction, including time‐resolved variants.
Martí Raya‐Moreno, Alexander Buccheri, Noah Alexy Dasch, Nasrin Farahani, Ignacio Gonzalez Oliva, Andris Gulans, Seokhyun Hong, Manoar Hossain, Hannah Kleine, Martin Kuban, Sven Lubeck, Benedikt Maurer, Pasquale Pavone, Fabian Peschel, Daria Popova‐Gorelova, Lu Qiao, Elias Richter, Santiago Rigamonti, Ronaldo Rodrigues Pela, Maximilian Schebek, Kshitij Sinha, Daniel T. Speckhard, Jan Stutz, Sebastian Tillack, Dmitry Tumakov, Jānis Užulis, Mara Voiculescu, Cecilia Vona, Mao Yang, Claudia Draxl   +29 more
wiley   +1 more source

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

Advanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li, Jin Ning, An Wang, Minxi Shi, Yuanze Chen, Guoliang Liu, Shiquan Sun   +6 more
wiley   +1 more source

BER-Constrained Power Allocation for Uplink NOMA Systems with One-Bit ADCs

Mathematics
This study investigates bit error rate (BER)-constrained power allocation for uplink non-orthogonal multiple access (NOMA) systems in which a base station employs one-bit analog-to-digital converters.
Tae-Kyoung Kim
doaj   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

CHCHD10 Mitigates Alzheimer's Disease‐Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons

Advanced Science, EarlyView.
CHCHD10 loss in Alzheimer's disease is associated with mitochondrial dysfunction, epigenomic disruption, and tau pathology. Restoration of CHCHD10 shifts DNA methylation toward a non‐disease state and reduces tau and amyloid pathology, with KATNAL2 acting as a downstream effector.
Teresa M. Thomas, Ching‐Yao Yang, Kexin Zhang, Liam Wetzel, Dina Bugybayeva, Julia Ferguson, Md Mahmudul Hasan, William Samsa, Nandita Patil, Anshul Dash, Tarini Gowda, Xiongwei Zhu, Feixiong Cheng, Tian Liu   +13 more
wiley   +1 more source

Performance Analysis of Pair-Wise Symbol Detection in Uplink NOMA-ISaC Systems

IEEE Open Journal of the Communications Society
This paper investigates the bit error rate (BER) and outage probability performance of integrated sensing and communication (ISaC) in uplink non-orthogonal multiple access (NOMA) systems. Specifically, we consider an ISaC framework where the radar signal
Haofeng Liu, Emad Alsusa, Arafat Al Dweik   +2 more
doaj   +1 more source