Results 81 to 90 of about 61,960 (301)
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies
We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli +8 more
wiley +1 more source
Particle filtering can be used to handle the non-liner and non-Gaussian problems,while the sequential importance resampling (SIR) algorithm can be better to solve the degeneracy phenomenon in particle filtering and be applied in the semiblind estimation ...
SHI Danfeng, ZHANG Jing
doaj
Improved Parallel Resampling Methods for Particle Filtering
Particle filter techniques are common methods used to estimate the evolving state of nonlinear, non-Gaussian time-variant systems by utilizing a periodic sequence of noisy measurements.
Matthew A. Nicely, B. Earl Wells
doaj +1 more source
Systemic dysregulation of apolipoproteins in amyotrophic lateral sclerosis serum
Amyotrophic lateral sclerosis (ALS) is a fatal disease that damages motor neurons. This study found that people with ALS show significant changes in blood fats and the proteins that carry them. Several apolipoproteins were higher, lipid balances were altered, and normal protein–lipid relationships were disrupted.
Finula I. Isik +6 more
wiley +1 more source
Stochastic Definition of State-Space Equation for Particle Filtering Algorithms
Particle Filtering is a nonlinear and non-Gaussian model-based Bayesian Filtering algorithm based on Monte Carlo Sampling techniques. This filtering methodology can be used to increase the reliability and the availability of the monitored system ...
M. Corbetta +3 more
doaj +1 more source
Performance Analysis of Generator Dynamic State Estimation under Uncertain Measurement
Random errors are unavoidable in phasor measurement unit (PMU), and the PMU measurement data may be uncertain in actual power system, such as delay, reordering or even missing.
Jingbo ZHAO +5 more
doaj +1 more source
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source
New Branching Filters With Explicit Negative Dependence
Particle filters are used to solve nonlinear filtering problems. We focus on the sampling step of a particle filter and present new algorithms that introduce explicit negative dependence between the number of particles reassigned at each location, with ...
Michael A. Kouritzin +2 more
doaj +1 more source
The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source

