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Article: Toward Deep Biophysical Cytometry: Prospects and Challenges

TitleToward Deep Biophysical Cytometry: Prospects and Challenges
Authors
Keywordsbiomolecular basis
biophysical cytometry
deep learning
multimodal cytometry
standardization
Issue Date1-Apr-2021
PublisherCell Press
Citation
Trends in Biotechnology, 2021, v. 39, n. 12, p. 1249-1262 How to Cite?
Abstract

The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.


Persistent Identifierhttp://hdl.handle.net/10722/340671
ISSN
2023 Impact Factor: 14.3
2023 SCImago Journal Rankings: 2.536
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLee, KCM-
dc.contributor.authorGuck, J-
dc.contributor.authorGoda, K-
dc.contributor.authorTsia, KK-
dc.date.accessioned2024-03-11T10:46:18Z-
dc.date.available2024-03-11T10:46:18Z-
dc.date.issued2021-04-01-
dc.identifier.citationTrends in Biotechnology, 2021, v. 39, n. 12, p. 1249-1262-
dc.identifier.issn0167-7799-
dc.identifier.urihttp://hdl.handle.net/10722/340671-
dc.description.abstract<p>The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.</p>-
dc.languageeng-
dc.publisherCell Press-
dc.relation.ispartofTrends in Biotechnology-
dc.subjectbiomolecular basis-
dc.subjectbiophysical cytometry-
dc.subjectdeep learning-
dc.subjectmultimodal cytometry-
dc.subjectstandardization-
dc.titleToward Deep Biophysical Cytometry: Prospects and Challenges-
dc.typeArticle-
dc.identifier.doi10.1016/j.tibtech.2021.03.006-
dc.identifier.scopuseid_2-s2.0-85109136909-
dc.identifier.volume39-
dc.identifier.issue12-
dc.identifier.spage1249-
dc.identifier.epage1262-
dc.identifier.eissn1879-3096-
dc.identifier.isiWOS:000718605300005-
dc.identifier.issnl1879-3096-

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