CryoVirusDB: A Labeled Cryo-EM Image Dataset for AI-Driven Virus Particle Picking.
CryoVirusDB: A Labeled Cryo-EM Image Dataset for AI-Driven Virus Particle Picking.
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CryoVirusDB：用于 AI 驱动的病毒颗粒挑选的标记 Cryo-EM 图像数据集。
DOI：
10.1101/2023.12.25.573312
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Cheng,Jianlin
中科院分区：
文献类型：
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作者：
Gyawali,Rajan;Dhakal,Ashwin;Wang,Liguo;Cheng,Jianlin
随着仪器、图像处理算法和计算能力的进步，单粒子电子冷冻显微镜(Cryo-EM)在确定病毒的三维结构方面已经达到了接近原子的分辨率。病毒结构在研究其生物学功能、推动抗病毒疫苗和治疗方法的发展中起着至关重要的作用。尽管人工智能(AI)在一般图像处理方面是有效的，但由于缺乏人工标记的高质量数据集，它在从冷冻-EM显微图像(图像)中识别和提取病毒颗粒方面的发展一直受到阻碍。为了填补这一空白，我们引入了CryoVirusDB，这是一个标记的数据集，包含了低温电子显微镜照片中专家挑选的病毒颗粒的坐标。CryoVirusDB包括9,941张9种不同病毒的显微照片以及339,398个标记的病毒颗粒的坐标。它可用于训练和测试人工智能和机器学习(例如，深度学习)方法，以准确识别低温电磁显微图像中的病毒颗粒，从而构建病毒的原子结构模型。
With the advancements in instrumentation, image processing algorithms, and computational capabilities, single-particle electron cryo-microscopy (cryo-EM) has achieved nearly atomic resolution in determining the 3D structures of viruses. The virus structures play a crucial role in studying their biological function and advancing the development of antiviral vaccines and treatments. Despite the effectiveness of artificial intelligence (AI) in general image processing, its development for identifying and extracting virus particles from cryo-EM micrographs (images) has been hindered by the lack of manually labelled high-quality datasets. To fill the gap, we introduce CryoVirusDB, a labeled dataset containing the coordinates of expert-picked virus particles in cryo-EM micrographs. CryoVirusDB comprises 9,941 micrographs of 9 different viruses along with the coordinates of 339,398 labeled virus particles. It can be used to train and test AI and machine learning (e.g., deep learning) methods to accurately identify virus particles in cryo-EM micrographs for building atomic 3D structural models for viruses.