Author

Fengqing Yu

Sunnybrook Health Science CentreORCID 0009-0008-3535-7356Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Ahmadreza AttarpouriD· 1 shared Ailey Crow· 1 shared Andrew S. ClappisoniD· 1 shared Barsin Eshaghi Gharagoz· 1 shared Benjamin Haibe‐KainsiD· 1 shared Bo WangiD· 1 shared Bojana StefanoviciD· 1 shared Braedyn AuiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperNeuroscience

Ahmadreza AttarpourORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintNov 14, 2025

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

Ahmadreza Attarpour, Misha Raffiee, Tony Xu…·Maged Goubran

MAPL3 enables whole-brain projectome mapping at single-axon resolution using deep learning and light sheet microscopy, outperforming existing methods across diverse datasets.

1 citation

imagingspatial transcriptomics

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BioinformaticsbioRxivPreprintJul 6, 2023

Reusability Report: Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients

Emily So, Fengqing Yu, Bo Wang, Benjamin Haibe‐Kains

This paper reproduces and improves the reusability of the TCRP method for predicting drug response across preclinical and clinical datasets.

DOI 10.1101/2023.07.06.547938

machine learning (classical)drug response / drug discovery

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