Author

L. A. Walsh

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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Cancer Biology· 1 Cell Biology· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Approach:experimental assay· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Assay:fluorescence / live-cell microscopy· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

B. Fiset· 3 shared A. Al-Ghabkari· 1 shared A. Arabzadeh· 1 shared A. Monast· 1 shared A. R. Maher· 1 shared C. T. Appleton· 1 shared D. F. Quail· 1 shared E. Karimi· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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3 shared papersPhysiology

B. Fiset

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Synovial macrophage activation mediates pain experiences in experimental knee osteoarthritis

G. Blackler, Y. Lai-Zhao, J. Klapak, H. T. Philpott, K. K. Pitchers, A. R. Maher, B. Fiset, L. A. Walsh, E. R. Gillies, C. T. Appleton

The study shows that targeting synovial macrophages via STAT6 inhibition reduces pain in experimental knee OA without worsening joint damage.

bioRxiv · Apr 25, 2023Physiology

Met-HER3 crosstalk supports proliferation via MPZL3 in MET-amplified cancer cells

Y. E. Stern, S. Duhamel, A. Al-Ghabkari, A. Monast, B. Fiset, F. Aboulizadeh, Z. Yao, I. Stagljar, L. A. Walsh, M. Park

The paper identifies a HER3-MPZL3 axis that supports proliferation in MET-amplified cancer cells through tyrosine phosphorylation and interaction.

Cellular and Molecular Life Sciences · Mar 5, 2022Peer-reviewedCancer Biology

Machine learning meets classical computer vision for accurate cell identification

E. Karimi, M. Rezanejad, B. Fiset, L. Perus, S. A. C. McDowell, A. Arabzadeh, G. Beugnot, P. Siegel, M.-C. Guiot, D. F. Quail, K. Siddiqi, L. A. Walsh

This paper introduces CIRCLE, a hybrid cell detection model that outperforms existing tools for accurate cell identification in 2D images.

bioRxiv · Feb 27, 2022 · PreprintCell Biology