Author

T. M. Fan

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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Bioengineering· 1 Cancer Biology· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 3 Approach:experimental assay· 2 Organism:mouse· 2 Research Focus:benchmarking· 1 Organism:chicken / avian· 1 Approach:deep learning· 1 Assay:imaging· 1 Assay:protein structure· 1

Frequent Co-Authors

K. L. Bailey· 2 shared A. B. Malik· 1 shared A. F. Gugliuzza· 1 shared A. Sheen· 1 shared C. Huang· 1 shared D. A. Llano· 1 shared D. Shukla· 1 shared E. Fink· 1 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersCancer Biology

K. L. Bailey

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Tumor-localized interleukin-2 and interleukin-12 combine with radiation therapy to safely potentiate regression of advanced malignant melanoma in pet dogs

J. A. Stinson, M. M. P. Barbosa, A. Sheen, N. Momin, E. Fink, J. Hampel, K. Selting, R. Kamerer, K. L. Bailey, K. D. Wittrup, T. M. Fan

This study evaluates collagen-binding IL-2 and IL-12 in pet dogs with melanoma, showing local and regional therapeutic responses that suggest potential human clinical benefit.

bioRxiv · Feb 12, 2024Cancer Biology

Engineered High-Affinity ACE2 Peptide Mitigates ARDS and Death Induced by Multiple SARS-CoV-2 Variants

L. Zhang, S. Dutta, S. Xiong, M. Chan, K. K. Chan, T. M. Fan, K. L. Bailey, M. Lindeblad, L. M. Cooper, L. Rong, A. F. Gugliuzza, D. Shukla, E. Procko, J. Rehman, A. B. Malik

This study shows an engineered ACE2 peptide effectively mitigates ARDS and death in mice infected with multiple SARS-CoV-2 variants.

bioRxiv · Dec 21, 2021Pharmacology & Toxicology

Localization free super-resolution microbubble velocimetry using a long short-term memory neural network

X. Chen, M. Lowerison, Z. Dong, N. C. Sekaran, C. Huang, S. Chen, T. M. Fan, D. A. Llano, P. Song

This paper introduces Deep-SMV, a deep learning-based method for super-resolution microbubble velocimetry that directly outputs blood velocity maps without requiring microbubble localization.

bioRxiv · Oct 1, 2021Bioengineering