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

Alexander Auer | Zendy; Maximilian T. Strauss | Zendy; Sebastian Strauss | Zendy; Ralf Jungmann | Zendy

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

Author(s) -

Alexander Auer,

Maximilian T. Strauss,

Sebastian Strauss,

Ralf Jungmann

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa154

Subject(s) - python (programming language) , computer science , software , mit license , graphical user interface , picasso , interface (matter) , documentation , artificial intelligence , computer graphics (images) , data mining , programming language , operating system , painting , art , bubble , maximum bubble pressure method , visual arts

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.

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