Suppr超能文献

用于3D单分子定位显微镜(SMLM)数据聚类的各向异性密度空间聚类算法(DBSCAN)

Anisotropic DBSCAN for 3D SMLM Data Clustering.

作者信息

Lörzing Pilar, Schake Philipp, Schlierf Michael

机构信息

B CUBE Center for Molecular Bioengineering, TU Dresden, Tatzberg 41, Dresden 01307, Germany.

Biotechnology Center (BIOTEC), CMCB, TU Dresden, Tatzberg 47-49, Dresden 01307, Germany.

出版信息

J Phys Chem B. 2024 Aug 22;128(33):7934-7940. doi: 10.1021/acs.jpcb.4c02030. Epub 2024 Aug 12.

Abstract

Single-molecule localization microscopy (SMLM) advanced biological discoveries beyond the diffraction limit. Various implementations enable 3D SMLM to reconstruct volumetric cell images. Yet, the inherent anisotropic point spread function of optical microscopes often limits the localization precision in the axial direction compared to the lateral precision. Such localization anisotropy could also expand spherical cellular structures to ellipsoidal cellular structures. Structure identification, however, is often performed using DBSCAN cluster algorithms, considering an isotropic search volume. Here, we show that an anisotropic DBSCAN search volume identifies anisotropic clusters more reliably using simulated ground truth data sets. Given experimental localization precisions, we suggest optimized search parameters based on an expanded computational grid search and show an enhanced performance of anisotropic DBSCAN amidst variations in localization precision. We demonstrate the capability of anisotropic DBSCAN on experimental data and anticipate that the algorithm allows for a more rigorous identification of clusters in cells, considering the anisotropic localization precisions of astigmatism-based 3D SMLM.

摘要

单分子定位显微镜(SMLM)推动了超越衍射极限的生物学发现。各种实现方式使三维SMLM能够重建细胞体积图像。然而,与横向精度相比,光学显微镜固有的各向异性点扩散函数常常限制轴向的定位精度。这种定位各向异性还可能将球形细胞结构扩展为椭圆形细胞结构。然而,结构识别通常使用DBSCAN聚类算法,考虑的是各向同性搜索体积。在这里,我们表明,使用模拟的真实数据集,各向异性DBSCAN搜索体积能更可靠地识别各向异性聚类。给定实验定位精度,我们基于扩展的计算网格搜索建议优化的搜索参数,并展示了在定位精度变化中各向异性DBSCAN的增强性能。我们在实验数据上展示了各向异性DBSCAN的能力,并预计该算法考虑基于像散的三维SMLM的各向异性定位精度,能够更严格地识别细胞中的聚类。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4a/11346466/44a74ad5fbca/jp4c02030_0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验