Author

Michael J. Parsons

Lunenfeld-Tanenbaum Research Institute

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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Bioinformatics· 1 Genetics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Approach:statistical model· 1 Organism:zebrafish· 1

Frequent Co-Authors

Aline Roch· 1 shared Allen GoodmaniD· 1 shared Amy KolbiD· 1 shared Anne Elizabeth CarpenteriD· 1 shared Anne Wilson· 1 shared Benjamin J. Toles· 1 shared Claire McQuin· 1 shared Holger HennigiD· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperBioinformatics

Aline Roch

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Generation of floxed alleles for cell-specific knockout in zebrafish

Masahiro Shin, Takayuki Nozaki, Benjamin J. Toles, Amy Kolb, Kevin Luk, Sumio Isogai, Kinji Ishida, Tomohito Hanasaka, Michael J. Parsons, Scot A. Wolfe, Nathan D. Lawson

The paper develops a protocol to generate floxed alleles in zebrafish for cell-specific knockout, demonstrating its utility in studying gene function.

bioRxiv · Sep 6, 2022 · PreprintGenetics

Label-free assessment of red blood cell storage lesions by deep learning

Minh Doan, Joseph A. Sebastian, Juan Carlos Caicedo, Stefanie Siegert, Aline Roch, Tracey R. Turner, Olga O. Mykhailova, Ruben N. Pinto, Claire McQuin, Allen Goodman, Michael J. Parsons, Olaf Wolkenhauer A, Holger Hennig, Shantanu Singh, Anne Wilson, , Anne Elizabeth Carpenter

This study uses deep learning and label-free imaging flow cytometry to classify red blood cell morphologies during storage, achieving 90% accuracy and predicting expiration dates based on morphological changes.

Proceedings of the National Academy of Sciences · Aug 24, 2020Peer-reviewedBioinformatics

Dissociable effects of visual crowding on the perception of colour and motion

John A. Greenwood, Michael J. Parsons

This study investigates whether visual crowding affects colour and motion perception independently, finding a double dissociation that suggests feature-specific disruption rather than a single process.

Proceedings of the National Academy of Sciences · Mar 19, 2020Peer-reviewedNeuroscience