Author

K. Mi

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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Microbiology· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:metagenomics· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:database / resource· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

X. Liu· 2 shared Z. Xu· 2 shared A. Huang· 1 shared H. Hao· 1 shared J. Li· 1 shared L. Huang· 1 shared P. Zhang· 1 shared Q. Zhang· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersMicrobiology

X. Liu

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

RFW captures species-level full profile of metagenomic functions via integrating genome annotation information

K. Mi, X. Liu

RFW improves microbial functional profiling by integrating genome annotations and taxonomic data, revealing new insights in disease-related microbiome analysis.

bioRxiv · Mar 19, 2024 · PreprintMicrobiology

Exploration of clinical breakpoint of Danofloxacin for Glaesserella parasuis in plasma and in PELF

Z. Xu, A. Huang, X. Luo, P. Zhang, L. Huang, X. Wang, K. Mi, S. Fang, X. Huang, J. Li, Z. Yuan, H. Hao

This study establishes three clinical breakpoint values for danofloxacin against Glaesserella parasuis using epidemiological, pharmacodynamic, and clinical data.

bioRxiv · Apr 15, 2021Microbiology

A framework for detecting and quantifying relationship alterations in microbial community

Z. Liu, K. Mi, Z. Xu, Q. Zhang, X. Liu

PM2RA detects and quantifies microbial relationship alterations between healthy and diseased states, showing higher specificity and sensitivity than co-occurrence-based methods.

bioRxiv · Apr 9, 2020Microbiology