Eric Vail

945 citations
37 papers · 501 · 1 hit paper · h-index 11

Impact in

Papers in

Eric Vail

33 papers receiving 489 citations

Eric Vail's Hit Papers

Emergence of a Novel SARS-CoV-2 Variant in Southern California 2021 · 227 citations
2270+1+3Years since publication50100150200

Peers

Eric Vail
Comparison fields: 5 of 63
  • Infectious Diseases 260
  • Modeling and Simulation 21
  • Gastroenterology 22
  • Animal Science and Zoology 39
  • Parasitology 22
Replace Ji‐Soo Kwon with:
Ji‐Soo Kwon South Korea
Thomas Kuntzen United States
Claudia Gandolfo Italy
Christina Großerichter-Wagener Netherlands
Tony Andréani France
Carole J. Henry Dunand United States
Mengyan Zhu China
Huawei Mao China
Rowa Y. Alhabbab Saudi Arabia
Shohreh Shahmahmoodi Iran
Eric Vail relative to Ji‐Soo Kwon South Korea Ji‐Soo Kwon's profile →
Citations per field
00.5×11×
Ji‐Soo Kwon · 1×
Citations per year

Countries citing papers authored by Eric Vail

Since Specialization
Citations

This map shows the geographic impact of Eric Vail's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eric Vail with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Vail more than expected).

Fields of papers citing papers by Eric Vail

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric Vail. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eric Vail. The network helps show where Eric Vail may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric Vail, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eric Vail Line = papers co-authored together Eric Vail links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Emergence of a Novel SARS-CoV-2 Variant in Southern California
Hit paper breakdown →
2021227
2 201536
3 202224
4 201524
5 201521
6 202020
7 202215
8 202114
9 202313
10 202011
11 202310
12 202110
13 20209
14 20238
15 20228
16 20167
17 20217
18 20205
19 20214
20 20224

About Eric Vail

Eric Vail is a scholar working on Oncology, Pulmonary and Respiratory Medicine, Infectious Diseases, Epidemiology and Cancer Research, having authored 37 papers that have together received 501 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (5 papers), Lung Cancer Treatments and Mutations (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Lung Cancer Research Studies (3 papers), Neuroblastoma Research and Treatments (2 papers), Oral and Maxillofacial Pathology (2 papers), Vector-borne infectious diseases (2 papers) and Respiratory viral infections research (2 papers). The work is most often cited by research in Infectious Diseases (260 citations), Modeling and Simulation (21 citations), Gastroenterology (22 citations), Animal Science and Zoology (39 citations) and Parasitology (22 citations). Eric Vail has collaborated with scholars based in United States, Philippines and Switzerland. Frequent co-authors include Wenjuan Zhang, Jasmine Plummer, Stephanie S. Chen, Brian Davis, John T. Fallon, Esther Yoon, Guiqing Wang, Xiaoyong Zheng, Ximing J. Yang and Ming Zhou. Their work appears in journals such as American Journal of Clinical Pathology, JCO Precision Oncology, Cancers, Journal of Cutaneous Pathology and Journal of Clinical Microbiology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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