Microscopy in infectious disease research

• Verfasst von: Laketa, Vibor [VerfasserIn]
• Titel: Microscopy in infectious disease research
• Titelzusatz: imaging across scales
• Verf.angabe: Vibor Laketa
• E-Jahr: 2018
• Jahr: 17 August 2018
• Umfang: 14 S.
• Fussnoten: Gesehen am 06.11.2019
• Titel Quelle: Enthalten in: Journal of molecular biology
• Ort Quelle: Amsterdam [u.a.] : Elsevier, 1959
• Jahr Quelle: 2018
• Band/Heft Quelle: 430(2018), 17, Seite 2612-2625
• ISSN Quelle: 1089-8638
• DOI: doi:10.1016/j.jmb.2018.06.018
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: CLEM
• Sach-SW: machine learning
• Sach-SW: SPIM
• Sach-SW: super-resolution light microscopy
• Sach-SW: virus
• K10plus-PPN: 168115448X

Abstract

A comprehensive understanding of host-pathogen interactions requires quantitative assessment of molecular events across a wide range of spatiotemporal scales and organizational complexities. Due to recent technical developments, this is currently only achievable with microscopy. This article is providing a general perspective on the importance of microscopy in infectious disease research, with a focus on new imaging modalities that promise to have a major impact in biomedical research in the years to come. Every major technological breakthrough in light microscopy depends on, and is supported by, advancements in computing and information technologies. Bioimage acquisition and analysis based on machine learning will pave the way toward more robust, automated and objective implementation of new imaging modalities and in biomedical research in general. The combination of novel imaging technologies with machine learning and near-physiological model systems promises to accelerate discoveries and breakthroughs in our understanding of infectious diseases, from basic research all the way to clinical applications.