James Tiedje: h-index, Total Citations, and Citation Map
James Tiedje's h-index is 195 (693 i10-index, 182,663+ total citations across 4+ publications) according to Google Scholar as of May 2026. James Tiedje is affiliated with University Distinguished Professor Emeritus, Michigan State University.
James Tiedje is a researcher affiliated with University Distinguished Professor Emeritus, Michigan State University, specializing in Microbiology, Soil science, Microbial Ecology. Their work has been cited 182,663 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
James Tiedje's Citation Metrics
Bibliometric impact based on 4 indexed publications.
- H-Index
- 195
- i10-Index
- 693
- Total Citations
- 182,663
- Citing Countries
- 23
As of May 2026.
James Tiedje has an h-index of 195 and 182,663 total citations across 4 publications, with research cited by institutions in 23 countries.
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Top Cited Works
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Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy
200722,262
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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 a Naïve Bayesian classifier for rapid rRNA sequence assignment into new bacterial taxonomy, a seminal method widely adopted for microbial identification.
The researcher developed improved alignments and new analytical tools for rRNA within the Ribosomal Database Project, establishing a widely adopted standard for microbial taxonomy.
The researcher established a critical quantitative framework linking DNA-DNA hybridization values to whole-genome sequence similarities, providing a foundational standard for microbial taxonomy.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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