Author

F. Mu

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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Cell Biology· 2 Cancer Biology· 1 Immunology· 1 Scientific Communication & Education· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Organism:human· 3 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1

Frequent Co-Authors

L. Liu· 3 shared S. Liu· 3 shared H. Chen· 2 shared X. Dong· 2 shared X. Xu· 2 shared Z. Li· 2 shared A. Chen· 1 shared A. Gitter· 1 shared

Activity by Year

2020-2022 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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Curved chords = mutual co-authorship

3 shared papersCell Biology

L. Liu

Mutual co-authors in cluster

Author profile →

5 papers

Recent·Most cited

Multi-omics analyses of single cell-derived colorectal cancer organoids reveal intratumor heterogeneity and immune response diversity

J. Yue, J. Li, Q. Xu, Q. Ma, C. Chen, S. Liu, H.-X. Sun, q. Sui, F. Mu, P. Ding, L. Liu, M. Perez-Moreno, X. Zhang

bioRxiv · Nov 25, 2022 · PreprintCancer Biology

Droplet microfluidics forward for tracing target cells at single-cell transcriptome resolution

Y. Liu, S. Wang, M. Lyu, R. Xie, W. Guo, Y. He, X. Shi, Y. Wang, J. Qi, Q. Zhu, H. Zhang, T. Luo, H. Chen, Y. Zhu, X. Dong, , Y. Liu

This paper develops a droplet-based method for single-cell transcriptome profiling of TCR-T cells, improving recovery and reducing contamination.

bioRxiv · Sep 13, 2022 · PreprintCell Biology

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

A. Chen, S. Liao, M. Cheng, K. Ma, L. Wu, Y. Lai, X. Qiu, J. Yang, W. Li, J. Xu, S. Hao, X. Wang, H. Lu, X. Chen, X. Liu, , J. Wang

This study develops Stereo-seq, a high-resolution spatial transcriptomic method, to analyze mouse organogenesis and map developmental disease loci.

Cell · May 1, 2022Peer-reviewedCell Biology

An approachable, flexible, and practical machine learning workshop for biologists

C. S. Magnano, F. Mu, R. S. Russ, M. Cvetkovic, D. Treu, A. Gitter

The ML4Bio workshop teaches biologists machine learning basics through a low-time, low-coding, and accessible approach, improving their confidence in applying ML in research.

bioRxiv · Feb 3, 2022Scientific Communication & Education

The expression of PDCD1 and CD274 in T cells and macrophages correlated positively with COVID-19 severity

Q. Gao, S. Liu, R. Ding, H. Chen, X. Dong, J. Xie, Y. Li, L. Chen, H. Liu, F. Mu

The paper analyzes public data to show that PDCD1 and CD274 expression in T cells and macrophages correlates with COVID-19 severity.

bioRxiv · Nov 17, 2020 · PreprintImmunology