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Analyzing complex single-molecule emission patterns with deep learning.

ABSTRACT: A fluorescent emitter simultaneously transmits its identity, location, and cellular context through its emission pattern. We developed smNet, a deep neural network for multiplexed single-molecule analysis to retrieve such information with high accuracy. We demonstrate that smNet can extract three-dimensional molecule location, orientation, and wavefront distortion with precision approaching the theoretical limit, and therefore will allow multiplexed measurements through the emission pattern of a single molecule.

SUBMITTER: Zhang P 

PROVIDER: S-EPMC6624853 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Analyzing complex single-molecule emission patterns with deep learning.

Zhang Peiyi P   Liu Sheng S   Chaurasia Abhishek A   Ma Donghan D   Mlodzianoski Michael J MJ   Culurciello Eugenio E   Huang Fang F  

Nature methods 20181030 11

A fluorescent emitter simultaneously transmits its identity, location, and cellular context through its emission pattern. We developed smNet, a deep neural network for multiplexed single-molecule analysis to retrieve such information with high accuracy. We demonstrate that smNet can extract three-dimensional molecule location, orientation, and wavefront distortion with precision approaching the theoretical limit, and therefore will allow multiplexed measurements through the emission pattern of a  ...[more]

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