Evaluation of methods for generative modeling of cell and nuclear shape | Zendy

Xiongtao Ruan | Zendy; Robert F. Murphy | Zendy

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Evaluation of methods for generative modeling of cell and nuclear shape

Author(s) -

Xiongtao Ruan,

Robert F. Murphy

Publication year - 2018

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/bty983

Subject(s) - interpolation (computer graphics) , computer science , artificial intelligence , software , spherical harmonics , generative model , shape analysis (program analysis) , linear interpolation , deep learning , pattern recognition (psychology) , algorithm , generative grammar , image (mathematics) , mathematics , mathematical analysis , static analysis , programming language

Cell shape provides both geometry for, and a reflection of, cell function. Numerous methods for describing and modeling cell shape have been described, but previous evaluation of these methods in terms of the accuracy of generative models has been limited.

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