Steve Self

5.2k citations
54 papers · 2.7k · 1 hit paper · h-index 24

Impact in

Papers in

    • HIV Research and Treatment 23
    • HIV/AIDS drug development and treatment 6
    • HIV/AIDS Research and Interventions 3

Steve Self

53 papers receiving 2.7k citations

Steve Self's Hit Papers

Tiered Categorization of a Diverse Panel of HIV-1 Env Pseudoviruses for Assessment of Neutralizing Antibodies 2009 · 446 citations
4460+5+11Years since publication100200300400

Peers

Steve Self
Comparison fields: 5 of 110
  • Virology 1.3k
  • Statistics and Probability 332
  • Infectious Diseases 630
  • Immunology 698
  • Cardiology and Cardiovascular Medicine 296
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Steve Self relative to Robin Mogg United States Robin Mogg's profile →
Citations per field
00.5×5.4×
Robin Mogg · 1×
Citations per year

Countries citing papers authored by Steve Self

Since Specialization
Citations

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

Fields of papers citing papers by Steve Self

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Tiered Categorization of a Diverse Panel of HIV-1 Env Pseudoviruses for Assessment of Neutralizing Antibodies
Hit paper breakdown →
2009446
2 2008402
3 2013194
4 2011183
5 1989166
6 199895
7 201092
8 201090
9 199382
10 200670
11 200063
12 201860
13 201659
14 201552
15 200446
16 200740
17 200138
18 199136
19 199935
20 200835

About Steve Self

Steve Self is a scholar working on Virology, Infectious Diseases, Molecular Biology, Statistics and Probability and Surgery, having authored 54 papers that have together received 2.7k indexed citations. Recurring topics across this work include HIV Research and Treatment (23 papers), HIV/AIDS drug development and treatment (6 papers), Hepatitis C virus research (6 papers), Viral Infections and Immunology Research (5 papers), vaccines and immunoinformatics approaches (5 papers), Immunotherapy and Immune Responses (4 papers), HIV/AIDS Research and Interventions (3 papers) and Esophageal Cancer Research and Treatment (3 papers). The work is most often cited by research in Virology (1.3k citations), Statistics and Probability (332 citations), Infectious Diseases (630 citations), Immunology (698 citations) and Cardiology and Cardiovascular Medicine (296 citations). Steve Self has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Blake Wood, Yudi Pawitan, William J. Huster, Ron Brookmeyer, David C. Montefiori, Peter B. Gilbert, Xuesong Yu, Michael S. Seaman, Jakob Armann and Lance Ching. Their work appears in journals such as PLoS ONE, Journal of Virology, JAIDS Journal of Acquired Immune Deficiency Syndromes, Biometrics and The Journal of Infectious Diseases.

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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