J Gregory Caporaso: h-index, Total Citations, and Citation Map
J Gregory Caporaso's h-index is 83 (159 i10-index, 171,045+ total citations across 3+ publications) according to Google Scholar as of May 2026. J Gregory Caporaso is affiliated with Northern Arizona University.
J Gregory Caporaso is a researcher affiliated with Northern Arizona University, specializing in microbiome, bioinformatics, software engineering. Their work has been cited 171,045 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
J Gregory Caporaso's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 83
- i10-Index
- 159
- Total Citations
- 171,045
- Citing Countries
- 20
As of May 2026.
J Gregory Caporaso has an h-index of 83 and 171,045 total citations across 3 publications, with research cited by institutions in 20 countries.
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We've mapped 5,000 of 171,045 citations for J Gregory Caporaso
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Global Impact Map
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Top Cited Works
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QIIME allows analysis of high-throughput community sequencing data
201038,776
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Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher developed QIIME, a foundational software framework that enabled the analysis of high-throughput community sequencing data, establishing a standard tool for microbiome research.
The researcher developed QIIME 2, a highly cited framework enabling reproducible, interactive, scalable, and extensible microbiome data science.
The researcher established a foundational framework for analyzing global microbial diversity at unprecedented sequencing depths, enabling standardized, large-scale ecological comparisons.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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