Jeff Fairman

1.2k citations
44 papers · 992 · h-index 21

Impact in

  • Hematology top 5%
    • Acute Myeloid Leukemia Research
    • Chronic Myeloid Leukemia Treatments
  • Virology top 10%

Papers in

Jeff Fairman

43 papers receiving 961 citations

Peers

Jeff Fairman
Comparison fields: 5 of 79
  • Hematology 193
  • Virology 54
  • Endocrinology 61
  • Microbiology 67
  • Infectious Diseases 188
Replace Jacinto López‐Sagaseta with:
Jacinto López‐Sagaseta Spain
Danilo Pellin United States
Yongshui Fu China
Koteswara R. Chintalacharuvu United States
Paola Paglia Italy
Anna Flace Switzerland
Stephen Henry New Zealand
Azad Kaushik Canada
Vanitha S. Raman United States
Fin J. Milder Netherlands
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Citations per field
00.5×1.5×2.3×
Jacinto López‐Sagaseta · 1×
Citations per year

Countries citing papers authored by Jeff Fairman

Since Specialization
Citations

This map shows the geographic impact of Jeff Fairman'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 Jeff Fairman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Fairman more than expected).

Fields of papers citing papers by Jeff Fairman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeff Fairman. 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 Jeff Fairman. The network helps show where Jeff Fairman may publish in the future.

Co-authors

The 25 scholars most cited alongside Jeff Fairman, 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 Jeff Fairman Line = papers co-authored together Jeff Fairman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998126
2 199562
3 202161
4 200557
5 199641
6 199439
7 200937
8 202136
9 200534
10 201834
11
Localization of SMAD5 and its evaluation as a candidate myeloid tumor suppressor.
199729
12 200927
13 200626
14 202026
15 199426
16
Inhibition of tumor growth correlates with the expression level of a human angiostatin transgene in transfected B16F10 melanoma cells.
199926
17 200924
18 201324
19 200923
20 202322

About Jeff Fairman

Jeff Fairman is a scholar working on Infectious Diseases, Epidemiology, Immunology, Molecular Biology and Hematology, having authored 44 papers that have together received 992 indexed citations. Recurring topics across this work include Viral gastroenteritis research and epidemiology (6 papers), Acute Myeloid Leukemia Research (6 papers), Immunotherapy and Immune Responses (5 papers), Escherichia coli research studies (5 papers), Streptococcal Infections and Treatments (4 papers), Immune Response and Inflammation (4 papers), Animal Virus Infections Studies (4 papers) and Reproductive tract infections research (4 papers). The work is most often cited by research in Hematology (193 citations), Virology (54 citations), Endocrinology (61 citations), Microbiology (67 citations) and Infectious Diseases (188 citations). Jeff Fairman has collaborated with scholars based in United States, Netherlands and Malawi. Frequent co-authors include Peter C. Nowell̀, David F. Claxton, L Nagarajan, Lalitha Nagarajan, Neeraj Kapoor, Liang Hong, Eric D. Green, Steven Dow, A. Craig Chinault and Ilya Chumakov. Their work appears in journals such as Vaccine, Blood, npj Vaccines, Vaccines and ACS Omega.

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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