Alison M Dunning: h-index, Total Citations, and Citation Map
Alison M Dunning's h-index is 128 (419 i10-index, 65,491+ total citations across 3+ publications) according to Google Scholar as of May 2026. Alison M Dunning is affiliated with Centre for Cancer Genetic Epidemiology, Dept of Oncology, University of Cambridge.
Alison M Dunning is a researcher affiliated with Centre for Cancer Genetic Epidemiology, Dept of Oncology, University of Cambridge, specializing in human genetics, cancer. Their work has been cited 65,491 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Alison M Dunning's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 128
- i10-Index
- 419
- Total Citations
- 65,491
- Citing Countries
- 18
As of May 2026.
Alison M Dunning has an h-index of 128 and 65,491 total citations across 3 publications, with research cited by institutions in 18 countries.
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Top Cited Works
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Genome-wide association study identifies novel breast cancer susceptibility loci
20072,927
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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 identified novel breast cancer susceptibility loci through a genome-wide association study, establishing a foundational reference for genetic risk analysis in the field.
The researcher identified 65 new breast cancer risk loci through association analysis, a seminal contribution that significantly expanded the known genetic architecture of the disease.
The researcher conducted a large-scale collaborative analysis linking breast cancer immunohistochemical subtypes to patient survival outcomes, establishing a foundational framework for subtype-specific prognostic assessment.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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