A Bayesian nonparametric approach to super-resolution single-molecule localization-Reference-Cited by-同舟云学术

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A Bayesian nonparametric approach to super-resolution single-molecule localization

Published:2021-12-01 Issue:4 Volume:15 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Gabitto Mariano I.¹,Marie-Nelly Herve²,Pakman Ari³,Pataki Andras¹,Darzacq Xavier²,Jordan Michael I.⁴

Affiliation:

1. Center for Computational Biology, Flatiron Institute, Simons Foundation

2. Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley

3. Department of Statistics and Center for Theretical Neuroscience, Columbia University

4. Department of Statistics, University of California, Berkeley

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fluorescence microscopy: A statistics-optics perspective;Reviews of Modern Physics;2024-06-05

2. A Bayesian Solution to Count the Number of Molecules within a Diffraction Limited Spot;2024-04-22

3. Toward quantitative super-resolution microscopy: molecular maps with statistical guarantees;Microscopy;2023-11-21

4. Super-resolution microscopy based on interpolation and wide spectrum de-noising;Computer Optics;2023-08

5. Diffraction-limited molecular cluster quantification with Bayesian nonparametrics;Nature Computational Science;2022-02-28

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