Zobrazeno 1 - 6
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pro vyhledávání: '"Georgeos Hardo"'
Publikováno v:
npj Imaging, Vol 2, Iss 1, Pp 1-16 (2024)
Abstract Time-resolved live-cell imaging using widefield microscopy is instrumental in quantitative microbiology research. It allows researchers to track and measure the size, shape, and content of individual microbial cells over time. However, the s
Externí odkaz:
https://doaj.org/article/68693bad0a3e4e44ba53f706ee85da76
Publikováno v:
BMC Biology, Vol 20, Iss 1, Pp 1-16 (2022)
Abstract Background Deep-learning–based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. However, the performance of any such model strictly depends on the quality and quan
Externí odkaz:
https://doaj.org/article/f30d2632f84141ec866cb7832128fdb5
Live cell imaging of microbial cells with microscopy has revolutionised quantitative microbiology. Micrographs are one of the most information-rich data types captured about a microbe, allowing quantification of the size and morphology of individual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::080c7530833d8c5ca8938d478ebd4d9e
https://doi.org/10.1101/2023.05.15.540883
https://doi.org/10.1101/2023.05.15.540883
Autor:
Georgeos Hardo, Somenath Bakshi
Publikováno v:
Essays in Biochemistry
Stochastic gene expression causes phenotypic heterogeneity in a population of genetically identical bacterial cells. Such non-genetic heterogeneity can have important consequences for the population fitness, and therefore cells implement regulation s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb9ac01814dea78ee149f0e4c39b2ec0
The performance of microbial communities exploited by industry are largely optimised by manipulating process parameters, such as flow rates, growth conditions, and reactor parameters. Conversely, the composition of microorganisms used are often viewe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c68d8252863cf2c7f7b3d922355f1302
https://doi.org/10.1101/543694
https://doi.org/10.1101/543694
Deep-learning based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. However, the performance of any such model strictly depends on the quality of training data, which is dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fccae155bb6d27ee593710094406631a
https://www.repository.cam.ac.uk/handle/1810/341952
https://www.repository.cam.ac.uk/handle/1810/341952