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  nanoTRON: a Picasso module for MLP-based classification of super-resolution data

Auer, A., Strauss, M. T., Strauss, S., & Jungmann, R. (2020). nanoTRON: a Picasso module for MLP-based classification of super-resolution data. BIOINFORMATICS, 36(11), 3620-3622. doi:10.1093/bioinformatics/btaa154.

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 Creators:
Auer, Alexander1, Author              
Strauss, Maximilian T.1, Author              
Strauss, Sebastian1, Author              
Jungmann, Ralf1, Author              
Affiliations:
1Jungmann, Ralf / Molecular Imaging and Bionanotechnology, Max Planck Institute of Biochemistry, Max Planck Society, ou_2149679              

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Free keywords: DNA; MICROSCOPY; KINETICS; BINDING
 Abstract: Motivation: Classification of images is an essential task in higher-level analysis of biological data. By bypassing the diffraction limit of light, super-resolution microscopy opened up a new way to look at molecular details using light microscopy, producing large amounts of data with exquisite spatial detail. Statistical exploration of data usually needs initial classification, which is up to now often performed manually. Results: We introduce nanoTRON, an interactive open-source tool, which allows super-resolution data classification based on image recognition. It extends the software package Picasso with the first deep learning tool with a graphic user interface.

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published in print
 Pages: 3
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 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: BIOINFORMATICS
Source Genre: Journal
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Publ. Info: GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND : OXFORD UNIV PRESS
Pages: - Volume / Issue: 36 (11) Sequence Number: - Start / End Page: 3620 - 3622 Identifier: ISSN: 1367-4803