Benjamin J. Doranz

17.0k total citations · 5 hit papers
104 papers, 9.2k citations indexed

About

Benjamin J. Doranz is a scholar working on Infectious Diseases, Immunology and Virology. According to data from OpenAlex, Benjamin J. Doranz has authored 104 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Infectious Diseases, 37 papers in Immunology and 34 papers in Virology. Recurrent topics in Benjamin J. Doranz's work include HIV Research and Treatment (34 papers), Mosquito-borne diseases and control (31 papers) and Immune Cell Function and Interaction (28 papers). Benjamin J. Doranz is often cited by papers focused on HIV Research and Treatment (34 papers), Mosquito-borne diseases and control (31 papers) and Immune Cell Function and Interaction (28 papers). Benjamin J. Doranz collaborates with scholars based in United States, Belgium and France. Benjamin J. Doranz's co-authors include Robert W. Doms, Joseph Rucker, Marc Parmentier, Michel Samson, Ronald G. Collman, Stephen C. Peiper, Robert Smyth, Yanjie Yi, Joanne F. Berson and Benhur Lee and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Benjamin J. Doranz

104 papers receiving 9.0k citations

Hit Papers

A Dual-Tropic Primary HIV... 1996 2026 2006 2016 1996 2013 2016 2018 2021 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Benjamin J. Doranz 4.2k 4.1k 3.5k 2.0k 2.0k 104 9.2k
Ali Amara 2.4k 0.6× 4.7k 1.2× 3.5k 1.0× 1.8k 0.9× 3.0k 1.5× 82 10.5k
Benhur Lee 4.3k 1.0× 5.3k 1.3× 4.1k 1.2× 3.3k 1.7× 896 0.5× 202 13.1k
Kalle Saksela 3.3k 0.8× 2.0k 0.5× 2.3k 0.6× 2.8k 1.4× 619 0.3× 123 7.6k
Yoshio Koyanagi 6.4k 1.5× 6.0k 1.5× 3.7k 1.0× 3.1k 1.6× 710 0.4× 222 12.8k
William A. Paxton 7.9k 1.9× 5.8k 1.4× 3.6k 1.0× 1.8k 0.9× 368 0.2× 88 10.3k
Sunny Choe 6.5k 1.5× 4.6k 1.1× 2.9k 0.8× 1.7k 0.9× 325 0.2× 10 8.4k
Per Johan Klasse 6.5k 1.5× 3.9k 1.0× 3.2k 0.9× 2.6k 1.3× 336 0.2× 153 9.4k
Paul R. Clapham 10.2k 2.4× 7.8k 1.9× 4.7k 1.3× 2.7k 1.4× 503 0.3× 127 14.4k
Masafumi Takiguchi 2.7k 0.6× 5.6k 1.4× 1.2k 0.3× 2.4k 1.2× 540 0.3× 269 8.9k
Mark B. Feinberg 7.3k 1.7× 6.4k 1.6× 3.9k 1.1× 2.1k 1.1× 627 0.3× 107 12.2k

Countries citing papers authored by Benjamin J. Doranz

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin J. Doranz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin J. Doranz. 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 Benjamin J. Doranz. The network helps show where Benjamin J. Doranz may publish in the future.

Co-authorship network of co-authors of Benjamin J. Doranz

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin J. Doranz. A scholar is included among the top collaborators of Benjamin J. Doranz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Benjamin J. Doranz. Benjamin J. Doranz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Phelan, Michael, et al.. (2023). 1431 Developing an FDA-qualified drug development tool, the membrane proteome array, for specificity testing of antibodies and CAR-T cell therapies. SHILAP Revista de lepidopterología. A1594–A1594. 1 indexed citations
3.
Banik, Soma S. R., Natasha Kushnir, Benjamin J. Doranz, & Ross Chambers. (2023). Breaking barriers in antibody discovery: harnessing divergent species for accessing difficult and conserved drug targets. mAbs. 15(1). 2273018–2273018. 3 indexed citations
4.
Tsuji, Isamu, Fue Vang, Jill A. Livengood, et al.. (2022). Somatic Hypermutation and Framework Mutations of Variable Region Contribute to Anti-Zika Virus-Specific Monoclonal Antibody Binding and Function. Journal of Virology. 96(11). e0007122–e0007122. 5 indexed citations
5.
Suryadevara, Naveenchandra, Swathi Shrihari, Pavlo Gilchuk, et al.. (2021). Neutralizing and protective human monoclonal antibodies recognizing the N-terminal domain of the SARS-CoV-2 spike protein. Cell. 184(9). 2316–2331.e15. 215 indexed citations breakdown →
6.
Collins, Matthew H., Ciara Gimblet, Ramesh Jadi, et al.. (2019). Human antibody response to Zika targets type-specific quaternary structure epitopes. JCI Insight. 4(8). 38 indexed citations
7.
Li, Leike, Weixu Meng, Melanie Horton, et al.. (2019). Potent neutralizing antibodies elicited by dengue vaccine in rhesus macaque target diverse epitopes. PLoS Pathogens. 15(6). e1007716–e1007716. 30 indexed citations
8.
Fox, Julie M., Vicky Roy, Bronwyn M. Gunn, et al.. (2019). Optimal therapeutic activity of monoclonal antibodies against chikungunya virus requires Fc-FcγR interaction on monocytes. Science Immunology. 4(32). 58 indexed citations
9.
Tucker, David, Jonathan T. Sullivan, Christine R. Fisher, et al.. (2018). Isolation of state-dependent monoclonal antibodies against the 12-transmembrane domain glucose transporter 4 using virus-like particles. Proceedings of the National Academy of Sciences. 115(22). E4990–E4999. 48 indexed citations
10.
Mousa, Jarrod J., Elad Binshtein, Stacey Human, et al.. (2018). Human antibody recognition of antigenic site IV on Pneumovirus fusion proteins. PLoS Pathogens. 14(2). e1006837–e1006837. 29 indexed citations
11.
Banik, Soma S. R., Xiaoxiang Deng, & Benjamin J. Doranz. (2017). Elevating the Value of mAbs using Epitope Mappings. Genetic Engineering & Biotechnology News. 37(15). 14–15. 2 indexed citations
12.
Messer, William B., Boyd L. Yount, Scott R. Royal, et al.. (2016). Functional Transplant of a Dengue Virus Serotype 3 (DENV3)-Specific Human Monoclonal Antibody Epitope into DENV1. Journal of Virology. 90(10). 5090–5097. 26 indexed citations
13.
Nivarthi, Usha K., Nurgun Kose, Gopal Sapparapu, et al.. (2016). Mapping the Human Memory B Cell and Serum Neutralizing Antibody Responses to Dengue Virus Serotype 4 Infection and Vaccination. Journal of Virology. 91(5). 39 indexed citations
14.
Banik, Soma S. R., et al.. (2016). Screening the Membrane Protein. Genetic Engineering & Biotechnology News. 36(15). 18–19. 3 indexed citations
15.
Doranz, Benjamin J. & Soma S. R. Banik. (2015). Optimizing Membrane Protein Expression. Genetic Engineering & Biotechnology News. 35(15). 20–21. 1 indexed citations
16.
Weiskopf, Daniela, Michael A. Angelo, Elzinandes Leal de Azeredo, et al.. (2013). Comprehensive analysis of dengue virus-specific responses supports an HLA-linked protective role for CD8 + T cells. Proceedings of the National Academy of Sciences. 110(22). E2046–53. 454 indexed citations breakdown →
17.
Payne, Riley, et al.. (2012). Maturation of the Gag core decreases the stability of retroviral lipid membranes. Virology. 433(2). 401–409. 9 indexed citations
18.
Rucker, Joseph, et al.. (2010). Measuring Membrane Protein Interactions Using Optical Biosensors. Methods in molecular biology. 617. 445–456. 6 indexed citations
19.
Doranz, Benjamin J., L G Filion, Francisco Díaz‐Mitoma, et al.. (2001). Safe Use of the CXCR4 Inhibitor ALX40-4C in Humans. AIDS Research and Human Retroviruses. 17(6). 475–486. 89 indexed citations
20.
Baik, Sarah, Robert W. Doms, & Benjamin J. Doranz. (1999). HIV and SIV gp120 Binding Does Not Predict Coreceptor Function. Virology. 259(2). 267–273. 41 indexed citations

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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