Margaret E. Ackerman

9.5k citations
159 papers · 4.6k · h-index 40

Impact in

  • Virology top 0.5%
    • HIV Research and Treatment
  • Immunology top 1%
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immunotherapy and Immune Responses

Papers in

Margaret E. Ackerman

147 papers receiving 4.5k citations

Peers

Margaret E. Ackerman
Comparison fields: 5 of 116
  • Virology 1.2k
  • Immunology 1.9k
  • Radiology, Nuclear Medicine and Imaging 1.8k
  • Infectious Diseases 876
  • Epidemiology 662
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Todd J. Suscovich United States
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Citations per field
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Citations per year

Countries citing papers authored by Margaret E. Ackerman

Since Specialization
Citations

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

Fields of papers citing papers by Margaret E. Ackerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Margaret E. Ackerman. 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 Margaret E. Ackerman. The network helps show where Margaret E. Ackerman may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 159 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013286
2 2010275
3 2016187
4 2012129
5 2017113
6 2014100
7 201188
8 200887
9 201987
10 201382
11 200979
12 201677
13 201477
14 202076
15 202175
16 201074
17 201673
18 200970
19 201170
20 201868

About Margaret E. Ackerman

Margaret E. Ackerman is a scholar working on Radiology, Nuclear Medicine and Imaging, Immunology, Molecular Biology, Virology and Epidemiology, having authored 159 papers that have together received 4.6k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (75 papers), HIV Research and Treatment (47 papers), Immune Cell Function and Interaction (31 papers), Glycosylation and Glycoproteins Research (29 papers), T-cell and B-cell Immunology (29 papers), Viral Infections and Immunology Research (15 papers), Complement system in diseases (11 papers) and vaccines and immunoinformatics approaches (11 papers). The work is most often cited by research in Virology (1.2k citations), Immunology (1.9k citations), Radiology, Nuclear Medicine and Imaging (1.8k citations), Infectious Diseases (876 citations) and Epidemiology (662 citations). Margaret E. Ackerman has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Galit Alter, Chris Bailey‐Kellogg, Anne‐Sophie Dugast, Austin W. Boesch, Eric P. Brown, K. Dane Wittrup, Todd J. Suscovich, Andrew R. Crowley, Anna F. Licht and Dan H. Barouch. Their work appears in journals such as The Journal of Infectious Diseases, Frontiers in Immunology, Journal of Immunological Methods, PLoS Pathogens and mAbs.

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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