WebCryoDRGN is a neural network-based method for heterogeneous reconstruction. Instead of discrete methods like 3D classification that produce an ensemble of K density … WebFeb 4, 2024 · Cryo-electron microscopy (cryo-EM) allows scientists to produce high-resolution, three-dimensional images of tiny molecules such as proteins. This technique works best for imaging proteins that exist in only one conformation, but MIT researchers have now developed a machine-learning algorithm that helps them identify multiple …

Uncovering structural ensembles from single-particle cryo …

WebJan 26, 2024 · 下面是作者0116在蚂蚁金服人工智能部的分享PPT,异质图神经网络:模型与应用,方便大家入门理解. Houye. 图神经网络（01）-图与图学习(上) 图（graph）近来正逐渐变成机器学习的一大核心领域，在开始PGL框架学习之前，我们先简单学习一下图论的基本概 … WebApr 3, 2024 · 研究人员提出了cryoDRGN，一种使用神经网络从异质单粒子cryo-EM数据集中重建3D密度图的方法。 这种方法的强大之处在于它能够表示异构结构，而无需简化关于 … hotels near oxford circus station

[1909.05215] Reconstructing continuous distributions of 3D …

WebNov 25, 2024 · Cryo-electron microscopy (cryo-EM) is unique among tools in structural biology in its ability to image large, dynamic protein complexes. Key to this ability is image processing algorithms for heterogeneous cryo-EM reconstruction, including recent deep learning-based approaches. The state-of-the-art method cryoDRGN uses a Variational … WebThe state-of-the-art method cryoDRGN uses a Variational Autoencoder (VAE) framework to learn a continuous distribution of protein structures from single particle cryo-EM imaging data. While cryoDRGN can model complex structural motions, the Gaussian prior distribution of the VAE fails to match the aggregate approximate posterior, which … WebCryoDRGN is a machine learning system for heterogenous cryo-EM reconstruction. In cryoDRGN’s framework of generative modeling, once a model is trained, an arbitrary number of volumes may be reconstructed, thus tools are needed to comprehensively explore the reconstructed distribution. This page describes a new “landscape analysis” … limitation of mapreduce