Author

R. P. Omran

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 2

Signature Assays, Organisms & Methods

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Organism:C. elegans· 2 Research Focus:cell type annotation· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

M. T. Hallett· 2 shared M. Whiteway· 2 shared S. Massahi· 2 shared S. Simpson· 2 shared V. Bettauer· 2 shared V. Dumeaux· 2 shared A. C. B. P. Costa· 1 shared A. C. Costa· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

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2 shared papersMicrobiology

M. T. Hallett

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Author profile →

2 papers

Recent·Most cited

Candida albicans exhibits heterogeneous and adaptive cytoprotective responses to anti-fungal compounds

V. Dumeaux, S. Massahi, V. Bettauer, S. S. Khurdia, A. C. B. P. Costa, R. P. Omran, S. Simpson, J. L. Xie, M. Whiteway, J. Berman, M. T. Hallett

This study characterizes the heterogeneous and adaptive cytoprotective responses of C. albicans to antifungal compounds using single-cell transcriptomics.

bioRxiv · Jul 20, 2022Microbiology

A deep learning approach to capture the essence of Candida albicans morphologies

V. Bettauer, A. C. Costa, R. P. Omran, S. Massahi, E. Kirbizakis, S. Simpson, V. Dumeaux, C. Law, M. Whiteway, M. T. Hallett

This paper develops a deep learning system called Candescence to detect and classify C. albicans morphologies from microscopy images using a curriculum-based learning strategy and GANs.

bioRxiv · Jun 10, 2021Microbiology