Asset Details
Do you wish to reserve the book?
Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images
Do you wish to request the book?
Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images
2019
Overview
Multicolor single-molecule localization super-resolution microscopy has enabled visualization of ultrafine spatial organizations of molecular assemblies within cells. Despite many efforts, current approaches for distinguishing and quantifying such organizations remain limited, especially when these are contained within densely distributed super-resolution data. In theory, higher-order correlation such as the Triple-Correlation function is capable of obtaining the spatial configuration of individual molecular assemblies masked within seemingly discorded dense distributions. However, due to their enormous computational cost such analyses are impractical, even for high-end computers. Here, we developed a fast algorithm for Triple-Correlation analyses of high-content multiplexed super-resolution data. This algorithm computes the probability density of all geometric configurations formed by every triple-wise single-molecule localization from three different channels, circumventing impractical 4D Fourier Transforms of the entire megapixel image. This algorithm achieves 10
2
-folds enhancement in computational speed, allowing for high-throughput Triple-Correlation analyses and robust quantification of molecular complexes in multiplexed super-resolution microscopy.
Analyzing the organization of molecular complexes in multi-color single-molecule localization microscopy data requires heavy computation resources that are impractical for laboratory computers. Here the authors develop a coordinate-based Triple-Correlation algorithm with improved speed and reduced computational cost.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
