Results 141 to 150 of about 9,171,861 (296)
Constructing Dynamic Functional Networks via Weighted Regularization and Tensor Low-Rank Approximation for Early Mild Cognitive Impairment Classification. [PDF]
Jiao Z, Ji Y, Zhang J, Shi H, Wang C.
europepmc +1 more source
Emerging experimental and computational methods for studying redox‐regulated structural transitions
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Encapsulins are protein nanocompartments that play an important role in iron storage. In the Myxococcus xanthus encapsulin system, two cargo proteins called EncB and EncC contribute to iron mineralization. Here, we show that EncB and EncC generate iron‐containing minerals with distinct chemical compositions, suggesting that the composition of stored ...
Harry B. McDowell +2 more
wiley +1 more source
Structural and biochemical analysis of a B12 superbinder
BtuG proteins are vitamin B12 scavengers in Bacteroides thetaiotaomicron, a dominant human gut bacterium. We present crystal structures of three BtuG homologs bound to cobalamin and its precursor cobinamide, revealing picomolar binding affinities, among the highest known for any natural protein.
Jose M. Martinez Felices +3 more
wiley +1 more source
Mycobacterial 3‐methylcrotonyl‐CoA carboxylase uses a mobile biotin‐carrying domain to shuttle a carboxyl group between two catalytic sites, enabling carboxylation of 3‐methylcrotonyl‐CoA during leucine breakdown. Cryo‐electron microscopy captures the carrier at both sites and reveals an inward loop movement that may prevent futile rebinding to the ...
Ajit Yadav +2 more
wiley +1 more source
Low-Rank Matrix Approximation with Stability [PDF]
Low-rank matrix approximation has been widely adopted in machine learning applications with sparse data, such as recommender systems. However, the sparsity of the data, incomplete and noisy, introduces challenges to the algorithm stability -small changes
Qin Lv +5 more
core
SAR Images Despeckling Using Subaperture Decomposition and Non-Local Low-Rank Tensor Approximation
Synthetic aperture radar (SAR) images suffer from speckle noise due to their imaging mechanism, which deteriorates image interpretability and hinders subsequent tasks like target detection and recognition.
Xinwei An +6 more
doaj +1 more source
The Shewanella oneidensis Fic enzyme SoFic targets the switch‐I region of EF‐Tu for AMPylation
Fic enzymes mediate diverse post‐translational modifications across all domains of life, including AMPylation. Prokaryotic EF‐Tu can be AMPylated and deAMPylated by the conserved Fic enzyme SoFic. Structural and biochemical approaches were used to characterize the effect of AMPylation on EF‐Tu, SoFic's enzymatic activities, and the enzyme‐target ...
Svenja Runge +6 more
wiley +1 more source
Error estimates for SUPG-stabilised Dynamical Low Rank Approximations [PDF]
We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems.
Nobile, Fabio +1 more
core +1 more source
Low-Rank Approximation, Adaptation, and Other Tales [PDF]
Low-rank approximation is a fundamental technique in modern data analysis, widely utilized across various fields such as signal processing, machine learning, and natural language processing.
Lu, Jun
core +1 more source

