Author

S. Michel-Mata

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· 1

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1 Assay:metagenomics· 1 Organism:mouse· 1 Organism:rat· 1

Frequent Co-Authors

H. Jia· 1 shared L. Dai· 1 shared M. T. Angulo· 1 shared S. T. Weiss· 1 shared X. He· 1 shared X.-W. Wang· 1 shared Y.-Y. Liu· 1 shared Z. Sun· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperMicrobiology

H. Jia

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1 paper

Recent·Most cited

Identifying keystone species in microbial communities using deep learning

X.-W. Wang, Z. Sun, H. Jia, S. Michel-Mata, M. T. Angulo, L. Dai, X. He, S. T. Weiss, Y.-Y. Liu

This paper introduces a deep learning framework to identify keystone species in microbial communities using synthetic and real microbiome data, finding taxa with high keystoneness show community specificity.

bioRxiv · Mar 15, 2023Microbiology