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Characterization of drug effects on cell cultures from phase-contrast microscopy images.
Barucic, Denis; Kaushik, Sumit; Kybic, Jan; Stanková, Jarmila; Dzubák, Petr; Hajdúch, Marián.
Afiliação
  • Barucic D; Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic. Electronic address: barucden@fel.cvut.cz.
  • Kaushik S; Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic. Electronic address: kaushsum@fel.cvut.cz.
  • Kybic J; Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic. Electronic address: kybic@fel.cvut.cz.
  • Stanková J; Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, Czech Republic.
  • Dzubák P; Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, Czech Republic.
  • Hajdúch M; Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Olomouc, Czech Republic.
Comput Biol Med ; 151(Pt A): 106171, 2022 12.
Article em En | MEDLINE | ID: mdl-36306582
ABSTRACT
In this work, we classify chemotherapeutic agents (topoisomerase inhibitors) based on their effect on U-2 OS cells. We use phase-contrast microscopy images, which are faster and easier to obtain than fluorescence images and support live cell imaging. We use a convolutional neural network (CNN) trained end-to-end directly on the input images without requiring for manual segmentations or any other auxiliary data. Our method can distinguish between tested cytotoxic drugs with an accuracy of 98%, provided that their mechanism of action differs, outperforming previous work. The results are even better when substance-specific concentrations are used. We show the benefit of sharing the extracted features over all classes (drugs). Finally, a 2D visualization of these features reveals clusters, which correspond well to known class labels, suggesting the possible use of our methodology for drug discovery application in analyzing new, unseen drugs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Técnicas de Cultura de Células Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Técnicas de Cultura de Células Idioma: En Ano de publicação: 2022 Tipo de documento: Article