Peter D. Burrows

5.2k total citations
98 papers, 4.1k citations indexed

About

Peter D. Burrows is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Peter D. Burrows has authored 98 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Immunology, 35 papers in Radiology, Nuclear Medicine and Imaging and 23 papers in Molecular Biology. Recurrent topics in Peter D. Burrows's work include T-cell and B-cell Immunology (61 papers), Immune Cell Function and Interaction (40 papers) and Monoclonal and Polyclonal Antibodies Research (35 papers). Peter D. Burrows is often cited by papers focused on T-cell and B-cell Immunology (61 papers), Immune Cell Function and Interaction (40 papers) and Monoclonal and Polyclonal Antibodies Research (35 papers). Peter D. Burrows collaborates with scholars based in United States, Egypt and Japan. Peter D. Burrows's co-authors include Max D. Cooper, Matthias Wabl, Hiromi Kubagawa, John F. Kearney, M D Cooper, Kohtaro Fujihashi, L G Billips, Jerry R. McGhee, Jiyang Wang and G. Larry Gartland and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Peter D. Burrows

98 papers receiving 3.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Peter D. Burrows United States	35	2.8k	1.1k	998	438	319	98	4.1k
Sylvia Miescher Switzerland	35	2.0k 0.7×	931 0.8×	1.0k 1.0×	651 1.5×	275 0.9×	102	3.6k
Henry H. Wortis United States	38	3.2k 1.1×	972 0.9×	718 0.7×	334 0.8×	386 1.2×	78	4.6k
Nobuo Sakaguchi Japan	37	2.7k 0.9×	1.9k 1.7×	514 0.5×	537 1.2×	206 0.6×	119	4.7k
Raul M. Torres United States	36	3.2k 1.1×	1.5k 1.3×	541 0.5×	492 1.1×	196 0.6×	103	4.9k
Lawrence J. Wysocki United States	28	2.6k 0.9×	1.1k 1.0×	1.4k 1.4×	216 0.5×	168 0.5×	60	3.5k
Ronald Palacios Sweden	40	3.2k 1.1×	1.5k 1.3×	838 0.8×	923 2.1×	274 0.9×	100	5.1k
Karen M. Haas United States	30	3.1k 1.1×	793 0.7×	865 0.9×	705 1.6×	332 1.0×	62	4.5k
E L Reinherz United States	29	2.6k 0.9×	750 0.7×	1.2k 1.3×	689 1.6×	195 0.6×	38	3.8k
M L Thomas United States	24	2.1k 0.7×	1.6k 1.4×	527 0.5×	392 0.9×	143 0.4×	31	3.6k
Mark J. Mamula United States	40	3.5k 1.2×	1.2k 1.1×	985 1.0×	555 1.3×	137 0.4×	86	5.8k

Countries citing papers authored by Peter D. Burrows

Since Specialization

Citations

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

Fields of papers citing papers by Peter D. Burrows

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter D. Burrows. 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 Peter D. Burrows. The network helps show where Peter D. Burrows may publish in the future.

Co-authorship network of co-authors of Peter D. Burrows

This figure shows the co-authorship network connecting the top 25 collaborators of Peter D. Burrows. A scholar is included among the top collaborators of Peter D. Burrows 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 Peter D. Burrows. Peter D. Burrows is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Harada, Yasuyo, Takanori Sasaki, Mariko Okada, et al.. (2023). Type 2 helper T cells convert into Interleukin-13-expressing follicular helper T cells after antigen repriming. 5(1). 1–12. 2 indexed citations

Rashid, Harunur, et al.. (2022). Loss of early B cell protein λ5 decreases bone mass and accelerates skeletal aging. Frontiers in Immunology. 13. 906649–906649. 1 indexed citations

Silva-Sánchez, Aarón, André M. Vale, Ada Elgavish, et al.. (2015). Violation of an Evolutionarily Conserved Immunoglobulin Diversity Gene Sequence Preference Promotes Production of dsDNA-Specific IgG Antibodies. PLoS ONE. 10(2). e0118171–e0118171. 15 indexed citations

Wang, Yuge, Robert Parks, Aarón Silva-Sánchez, et al.. (2015). HIV-1 gp140 epitope recognition is influenced by immunoglobulin DH gene segment sequence. Immunogenetics. 68(2). 145–155. 11 indexed citations

Burrows, Peter D., Teresa Santiago, Olga Y. Volkova, et al.. (2011). FCRLA is an intracellular FcR-related protein that binds IgM, IgG and IgA isotypes in B cells (45.11). The Journal of Immunology. 186(1_Supplement). 45.11–45.11. 1 indexed citations

Masuda, Keiji, et al.. (2010). Defining the immunological phenotype of Fc receptor-like B (FCRLB) deficient mice: Confounding role of the inhibitory FcγRIIb. Cellular Immunology. 266(1). 24–31. 6 indexed citations

Conley, Mary Ellen & Peter D. Burrows. (2010). Plugging the Leaky Pre-B Cell Receptor. The Journal of Immunology. 184(3). 1127–1129. 7 indexed citations

Masuda, Keiji, Randall S. Davis, Takako Maruyama, et al.. (2005). FcRY, an Fc receptor related gene differentially expressed during B lymphocyte development and activation. Gene. 363. 32–40. 14 indexed citations

Zhang, Zhixin, Peter D. Burrows, & Max D. Cooper. (2004). The molecular basis and biological significance of V_H replacement. Immunological Reviews. 197(1). 231–242. 39 indexed citations

10.

Coffey, Tom, et al.. (2003). Analysing the security of a non-repudiation communication protocol with mandatory proof of receipt. 351–356. 2 indexed citations

11.

Burrows, Peter D., et al.. (2002). B Cell-Restricted Human mb-1 Gene: Expression, Function, and Lineage Infidelity. Immunologic Research. 26(1-3). 35–44. 5 indexed citations

12.

Mason, Dean T., et al.. (2001). CREATOR TO CONSUMER IN A DIGITAL AGE AUSTRALIAN BOOK PRODUCTION IN TRANSITION. Livestock Science. 234. 103976–103976. 6 indexed citations

13.

Burrows, Peter D. & Max D. Cooper. (1997). B cell development and differentiation. Current Opinion in Immunology. 9(2). 239–244. 87 indexed citations

14.

Lydyard, Peter M., et al.. (1994). Lymphopoiesis today. Immunology Today. 15(6). 255–257. 2 indexed citations

15.

Burrows, Peter D., John F. Kearney, Harry W. Schroeder, & Max D. Cooper. (1993). 3 Normal B lymphocyte differentiation. Baillière s Clinical Haematology. 6(4). 785–806. 7 indexed citations

16.

Burrows, Peter D., et al.. (1993). B-cell development in man. Current Opinion in Immunology. 5(2). 201–206. 17 indexed citations

17.

Burrows, Peter D., et al.. (1991). Differences in Human B Cell Differentiation. Advances in experimental medicine and biology. 292. 215–226. 2 indexed citations

18.

Roncella, Silvio, Dunia Ramarli, Marco Forni, et al.. (1990). Establishment of an EBV‐positive lymphoblastoid cell line that grows as a lymphoma in nude mice and expresses membrane CD2 molecules. International Journal of Cancer. 45(2). 299–307. 16 indexed citations

19.

Bertoli, Luigi F. & Peter D. Burrows. (1988). Normal B-Lineage Cells: Their Differentiation and Identification. Clinics in Laboratory Medicine. 8(1). 15–30. 5 indexed citations

20.

Burrows, Peter D., John F. Kearney, Alexander R. Lawton, & Max D. Cooper. (1978). Pre-B Cells: Bone Marrow Persistence in Anti-µ-Suppressed Mice, Conversion to B Lymphocytes, and Recovery after Destruction by Cyclophosphamide. The Journal of Immunology. 120(5). 1526–1531. 57 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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