Author

C.-M. K. Li

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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Immunology· 2 Cell Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Organism:human· 3 Research Focus:cell-cell communication· 2 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:scRNA-seq· 2 Approach:benchmark study· 1

Frequent Co-Authors

H. Zhou· 2 shared S. Wang· 2 shared T. M. Yamawaki· 2 shared A. Bredemeyer· 1 shared A. Fu· 1 shared A. L. Koenig· 1 shared A. Pipathsouk· 1 shared B. Ason· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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2 shared papersCell Biology

H. Zhou

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Author profile →

3 papers

Recent·Most cited

AN ARTIFICIAL INTELLIGENCE FOR RAPID IN-LINE LABEL-FREE HUMAN PLURIPOTENT STEM CELL COUNTING AND QUALITY ASSESSMENT

B. L. Ragunton, S. Van Buskirk, D. Wakefield, N. Randive, A. Pipathsouk, B. Pei, H. Zhou, T. M. Yamawaki, M. Berke, C.-M. K. Li, C. Hale, S. Wang, S. Chambers

This paper develops an AI algorithm for counting and assessing human pluripotent stem cells in brightfield images, achieving high accuracy and efficiency.

bioRxiv · Mar 20, 2023 · PreprintCell Biology

Targeting the Immune-Fibrosis Axis in Myocardial Infarction and Heart Failure

J. M. Amrute, X. Luo, V. Penna, A. Bredemeyer, T. Yamawaki, G. S. Heo, S. Shi, A. L. Koenig, S. Yang, F. F. Kadyrov, C. Jones, C. Kuppe, B. Kopecky, S. Hayat, P. Ma, , K. Lavine

The paper identifies a fibroblast trajectory associated with cardiac fibrosis and shows that macrophage-fibroblast crosstalk via IL-1β signaling drives fibrosis.

bioRxiv · Oct 17, 2022 · PreprintImmunology

Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

T. M. Yamawaki, D. R. Lu, D. C. Ellwanger, D. Bhatt, P. Manzanillo, H. Zhou, O. K. Yoon, O. Homann, S. Wang, C.-M. K. Li

This study benchmarks seven single-cell RNA-seq methods for immune cell profiling, finding that 10x Genomics 5 v1 and 3 v3 show higher sensitivity and fewer drop-out events.

bioRxiv · Sep 4, 2020Immunology