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Knowledge of a protein's atomic conformational ensemble is critical to determining its function, yet state-of-the-art ensemble prediction models are limited by lack of high-quality conformational data from simulation or experiment. Recent…

Machine Learning · Computer Science 2026-05-12 Jay Shenoy , Miro Astore , Axel Levy , Frédéric Poitevin , Sonya M. Hanson , Gordon Wetzstein

The past decade's "cryoEM revolution" has produced exponential growth in high-resolution structural data through advances in cryogenic electron microscopy (cryoEM) and tomography (cryoET). Deep learning integration into structural…

Quantitative Methods · Quantitative Biology 2025-07-29 Brady K. Zhou , Jason J. Hu , Jane K. J. Lee , Z. Hong Zhou , Demetri Terzopoulos

Recent advances in distance-based protein folding have led to a paradigm shift in protein structure prediction. Through sufficiently precise estimation of the inter-residue distance matrix for a protein sequence, it is now feasible to…

Biomolecules · Quantitative Biology 2021-01-27 Andrew McGehee , Sutanu Bhattacharya , Rahmatullah Roche , Debswapna Bhattacharya

Cryo-electron microscopy (Cryo-EM) enables high-resolution imaging of biomolecules, but structural heterogeneity remains a major challenge in 3D reconstruction. Traditional methods assume a discrete set of conformations, limiting their…

Machine Learning · Statistics 2025-09-09 Diego Sanchez Espinosa , Erik H Thiede , Yunan Yang

Cryo-electron microscopy (cryo-EM) is an emerging experimental method to characterize the structure of large biomolecular assemblies. Single particle cryo-EM records 2D images (so-called micrographs) of projections of the three-dimensional…

Applications · Statistics 2013-12-02 Mikhail Langovoy , Michael Habeck , Bernhard Schoelkopf

A novel approach for structure alignment is presented, where the key ingredients are: (1) An error function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. (2)…

Biological Physics · Physics 2007-05-23 M. Ohlsson , C. Peterson , M. Ringner , R. Blankenbecler

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep…

Quantitative Methods · Quantitative Biology 2016-05-09 Feng Wang , Huichao Gong , Gaochao liu , Meijing Li , Chuangye Yan , Tian Xia , Xueming Li , Jianyang Zeng

Programmable self-assembly has recently enabled the creation of complex structures through precise control of the interparticle interactions and the particle geometries. Targeting ever more structurally complex, dynamic, and functional…

We introduce a differential visual similarity metric to train deep neural networks for 3D reconstruction, aimed at improving reconstruction quality. The metric compares two 3D shapes by measuring distances between multi-view images…

Graphics · Computer Science 2020-04-02 Jiongchao Jin , Akshay Gadi Patil , Zhang Xiong , Hao Zhang

Cryo-electron microscopy (cryo-EM) is a powerful imaging technique for reconstructing three-dimensional molecular structures from noisy tomographic projection images of randomly oriented particles. We introduce a new data fusion framework,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Joe Kileel , Oscar Mickelin , Amit Singer , Sheng Xu

We propose a surface fitting method for unstructured 3D point clouds. This method, called DeepFit, incorporates a neural network to learn point-wise weights for weighted least squares polynomial surface fitting. The learned weights act as a…

Computer Vision and Pattern Recognition · Computer Science 2020-03-25 Yizhak Ben-Shabat , Stephen Gould

High-fidelity electron microscopy simulations required for quantitative crystal structure refinements face a fundamental challenge: while physical interactions are well-described theoretically, real-world experimental effects are…

Cryogenic electron microscopy (cryo-EM) provides a unique opportunity to study the structural heterogeneity of biomolecules. Being able to explain this heterogeneity with atomic models would help our understanding of their functional…

The recent breakthrough of AlphaFold3 in modeling complex biomolecular interactions, including those between proteins and ligands, nucleotides, or metal ions, creates new opportunities for protein design. In so-called inverse protein…

Biomolecules · Quantitative Biology 2025-07-22 Kai Yi , Kiarash Jamali , Sjors H. W. Scheres

Cryo-EM is a transformational paradigm in molecular biology where computational methods are used to infer 3D molecular structure at atomic resolution from extremely noisy 2D electron microscope images. At the forefront of research is how to…

Quantitative Methods · Quantitative Biology 2025-06-12 Shayan Shekarforoush , David B. Lindell , Marcus A. Brubaker , David J. Fleet

In recent years, Denoising Diffusion Models have demonstrated remarkable success in generating semantically valuable pixel-wise representations for image generative modeling. In this study, we propose a novel end-to-end framework, called…

Image and Video Processing · Electrical Eng. & Systems 2023-03-21 Zhaohu Xing , Liang Wan , Huazhu Fu , Guang Yang , Lei Zhu

The Cryo-EM 3D particle reconstruction is essential for identifying protein and uncover the biological mechanism of the macro-molecules. In this paper, we use Kam method for reconstruction. Kam method is \textit{ab-initio}, and it assumes…

Quantitative Methods · Quantitative Biology 2019-06-21 Yin Xian

Virtual try-on (VTON) aims to synthesize realistic images of a person wearing a target garment, with broad applications in e-commerce and digital fashion. While recent advances in latent diffusion models have substantially improved visual…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Xiang Xu

Single-particle cryo-Electron Microscopy (EM) has become a popular technique for determining the structure of challenging biomolecules that are inaccessible to other technologies. Recent advances in automation, both in data collection and…

Computer Vision and Pattern Recognition · Computer Science 2021-05-31 Ye Zhou , Amit Moscovich , Tamir Bendory , Alberto Bartesaghi

In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases…

Quantitative Methods · Quantitative Biology 2022-10-18 August George , Doo Nam Kim , Trevor Moser , Ian T. Gildea , James E. Evans , Margaret S. Cheung
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