The increasing interest in modeling the dynamics of ever larger proteins has revealed a fundamental problem with models that describe the molecular system as being in a global configuration state. This notion limits our ability to gather sufficient s...
Current opinion in structural biology
Oct 21, 2022
Integrative structural modeling enables structure determination of macromolecules and their complexes by integrating data from multiple sources. It has been successfully used to characterize macromolecular structures when a single structural biology ...
BACKGROUND: Despite recent advances in cellular cryo-electron tomography (CET), developing automated tools for macromolecule identification in submolecular resolution remains challenging due to the lack of annotated data and high structural complexit...
Journal of computer-aided molecular design
Aug 26, 2022
Molecular visualization is a cornerstone of structural biology, providing insights into the form and function of biomolecules that are difficult to achieve any other way. Scientific analysis, publication, education, and outreach often benefit from ph...
The combination of image analysis and superresolution microscopy methods allows for unprecedented insight into the organization of macromolecular assemblies in cells. Advances in deep learning (DL)-based object recognition enable the automated proces...
Journal of chemical information and modeling
Mar 30, 2022
Conformational sampling of protein structures is essential for understanding biochemical functions and for predicting thermodynamic properties such as free energies. Where previous approaches rely on sequential sampling procedures, recent development...
Journal of chemical information and modeling
Mar 29, 2022
We report for the first time the use of experimental electron density (ED) in the Protein Data Bank for modeling of noncovalent interactions (NCIs) for protein-ligand complexes. Our methodology is based on reduced electron density gradient (RDG) theo...
PURPOSE: To develop a Bayesian convolutional neural network (BCNN) with Monte Carlo dropout sampling for metabolite quantification with simultaneous uncertainty estimation in deep learning-based proton MRS of the brain.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2022
Cryo-electron tomography, combined with subtomogram averaging (STA), can reveal three-dimensional (3D) macromolecule structures in the near-native state from cells and other biological samples. In STA, to get a high-resolution 3D view of macromolecul...
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