Author

Dmytro Fishman

University of TartuORCID 0000-0002-4644-8893Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Assay:imaging· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:dimensionality reduction· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

Leopold PartsiD· 3 shared Kaupo PaloiD· 2 shared Ago RinkeniD· 1 shared Alexander Schreiner· 1 shared Benjamin Grys· 1 shared Brenda AndrewsiD· 1 shared Brittany M. Greco· 1 shared Charles M. BooneiD· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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3 shared papersBioinformatics

Leopold PartsORCID

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Author profile →

4 papers

Recent·Most cited

Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retention

Rohan Dandage, Mikhail Papkov, Brittany M. Greco, Dmytro Fishman, Helena Friesen, Kyle E. Wang, Erin B. Styles, Oren Z. Kraus, Benjamin Grys, Charles M. Boone, Brenda Andrews, Leopold Parts, Elena Kuzmin

This study uses single-cell imaging to analyze protein dynamics in response to paralog deletion, revealing mechanisms of gene retention and functional divergence.

bioRxiv · Nov 23, 2023 · PreprintSystems Biology

ArtSeg: Rapid Artifact Segmentation and Removal in Brightfield Cell Microscopy Images

Mohammed A. S. Ali, Kaspar Hollo, Tõnis Laasfeld, Jane Torp, Maris‐Johanna Tahk, Ago Rinken, Kaupo Palo, Leopold Parts, Dmytro Fishman

ArtSeg uses a deep learning model to automatically segment and remove artifacts from brightfield microscopy images using image-level labels, improving downstream analysis without requiring pixel-level annotations.

Scientific Reports · Jul 6, 2022Peer-reviewedBioinformatics

PAWER: Protein Array Web ExploreR

Dmytro Fishman, Ivan Kuzmin, Priit Adler, Jaak Vilo, Hedi Peterson

PAWER is an online tool that streamlines protein microarray analysis by integrating preprocessing, differential expression, and functional enrichment into a user-friendly interface, with an accompanying R package for advanced use.

BMC Bioinformatics · Sep 17, 2020Peer-reviewedBioinformatics

Segmenting nuclei in brightfield images with neural networks

Dmytro Fishman, Sten‐Oliver Salumaa, Daniel Majoral, Samantha E. Peel, Jan Wildenhain, Alexander Schreiner, Kaupo Palo, Leopold Parts

This paper demonstrates accurate nucleus segmentation from brightfield images using deep learning, showing that three CNN architectures can achieve this with U-Net performing best.

bioRxiv · Sep 10, 2019 · PreprintBioinformatics