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Characterization of drug effects on cell cultures from phase-contrast microscopy images

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15110%2F22%3A73615819" target="_blank" >RIV/61989592:15110/22:73615819 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21230/22:00360157

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0010482522008794?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0010482522008794?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.compbiomed.2022.106171" target="_blank" >10.1016/j.compbiomed.2022.106171</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Characterization of drug effects on cell cultures from phase-contrast microscopy images

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    COMPUTERS IN BIOLOGY AND MEDICINE

  • ISSN

    0010-4825

  • e-ISSN

    1879-0534

  • Volume of the periodical

    151

  • Issue of the periodical within the volume

    December 2022

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    8

  • Pages from-to

    106171

  • UT code for WoS article

    000885971100003

  • EID of the result in the Scopus database

    2-s2.0-85140305228