Author

Misha Raffiee

Howard Hughes Medical 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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Neuroscience· 1

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Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Organism:mouse· 1 Assay:spatial transcriptomics· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Ahmadreza AttarpouriD· 1 shared Ailey Crow· 1 shared Andrew S. ClappisoniD· 1 shared Barsin Eshaghi Gharagoz· 1 shared Bojana StefanoviciD· 1 shared Braedyn AuiD· 1 shared Fengqing YuiD· 1 shared Isabelle AubertiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperNeuroscience

Ahmadreza AttarpourORCID

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1 paper

Recent·Most cited

Quantitative profiling of whole-brain connectomes at single-axon resolution using deep learning and high-resolution light sheet microscopy

Ahmadreza Attarpour, Misha Raffiee, Tony Xu, Jonas Osmann, Shruti B Patel, Fengqing Yu, Braedyn Au, Andrew S. Clappison, Mahdi Biparva, Rui Zhu, Ailey Crow, Barsin Eshaghi Gharagoz, Matthew W Rozak, Isabelle Aubert, JoAnne McLaurin, , Maged Goubran

This paper introduces MAPL3, a deep learning pipeline for mapping whole-brain connectomes at single-axon resolution, demonstrating its effectiveness in analyzing orbitofrontal cortex circuitry.

bioRxiv · Nov 14, 2025 · PreprintNeuroscience