A deep learning and novelty detection framework for rapid phenotyping in high-content screening.
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ABSTRACT:
SUBMITTER: Sommer C
PROVIDER: S-EPMC5687041 | biostudies-literature | 2017 Nov
REPOSITORIES: biostudies-literature
Publications
A deep learning and novelty detection framework for rapid phenotyping in high-content screening.
Sommer Christoph C Hoefler Rudolf R Samwer Matthias M Gerlich Daniel W DW
Molecular biology of the cell 20170927 23
Supervised machine learning is a powerful and widely used method for analyzing high-content screening data. Despite its accuracy, efficiency, and versatility, supervised machine learning has drawbacks, most notably its dependence on a priori knowledge of expected phenotypes and time-consuming classifier training. We provide a solution to these limitations with <i>CellCognition Explorer</i>, a generic novelty detection and deep learning framework. Application to several large-scale screening data ...[more]
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