Machine Learning For Microbiome Data
Machine Learning for Microbiome Data is a computational methodology that applies machine learning algorithms to microbiome datasets to infer patterns, relationships, or predictions specific to microbial community structure and function, distinguished by its integration of high-dimensional biological data with statistical learning techniques for hypothesis generation, classification, or regression in microbiome research.
123
Publications
5.7K
Citations
762
Authors
403
Institutions
Publications per year
2017–2026
114
Parents
123
MicrobiotaProcess: A comprehensive R package for deep mining microbiome
Shuangbin Xu, Li Zhan, Wenli Tang et al. · The Innovation · 2023 · 276 citations · Full text
Major data analysis errors invalidate cancer microbiome findings
Abraham Gihawi, Yuchen Ge, Jennifer Lu et al. · mBio · 2023 · 201 citations · Full text
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Harvard University
Cambridge, United States
7 h-index
14 publications
478 citations
Utrecht University
Utrecht, The Netherlands
5 h-index
12 publications
750 citations
Stanford University
Stanford, United States
5 h-index
32 publications
680 citations
University of Bari Aldo Moro
Bari, Italy
5 h-index
26 publications
1K citations

Huazhong University of Science and Technology
Wuhan, China
4 h-index
27 publications
828 citations
University of Michigan
Ann Arbor, United States
4 h-index
26 publications
520 citations
Fred Hutch Cancer Center
Seattle, United States
4 h-index
26 publications
528 citations

University of Toronto
Toronto, Canada
4 h-index
7 publications
367 citations
1–8 of 403
8 publications · 519 citations
8
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6 publications · 305 citations
6
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5 publications · 148 citations
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5 publications · 166 citations
5
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5 publications · 162 citations
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