Peter R. Wilker

1.8k total citations
16 papers, 1.3k citations indexed

About

Peter R. Wilker is a scholar working on Epidemiology, Immunology and Hematology. According to data from OpenAlex, Peter R. Wilker has authored 16 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Epidemiology, 6 papers in Immunology and 4 papers in Hematology. Recurrent topics in Peter R. Wilker's work include Influenza Virus Research Studies (6 papers), Respiratory viral infections research (5 papers) and Platelet Disorders and Treatments (3 papers). Peter R. Wilker is often cited by papers focused on Influenza Virus Research Studies (6 papers), Respiratory viral infections research (5 papers) and Platelet Disorders and Treatments (3 papers). Peter R. Wilker collaborates with scholars based in United States, China and Japan. Peter R. Wilker's co-authors include Kenneth M. Murphy, Masako Kohyama, Daniel W. Bougie, Theresa L. Murphy, Richard H. Aster, Wataru Ise, Brian T. Edelson, Kai Hildner, William A. Frazier and Yoshihiro Kawaoka and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Peter R. Wilker

16 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Peter R. Wilker United States	13	535	303	300	251	182	16	1.3k
Hill Gaston United Kingdom	22	721 1.3×	349 1.2×	429 1.4×	127 0.5×	94 0.5×	38	1.5k
Chad Storer United States	12	414 0.8×	314 1.0×	516 1.7×	120 0.5×	164 0.9×	18	1.5k
Prasad Rallabhandi United States	18	747 1.4×	548 1.8×	618 2.1×	82 0.3×	254 1.4×	28	1.8k
Shoutaro Tsuji Japan	22	1.1k 2.1×	356 1.2×	566 1.9×	58 0.2×	116 0.6×	68	2.0k
Jordan P. Metcalf United States	26	565 1.1×	505 1.7×	518 1.7×	71 0.3×	72 0.4×	67	1.6k
Mary Renshaw United States	13	653 1.2×	629 2.1×	203 0.7×	114 0.5×	46 0.3×	17	1.3k
Elodie Mohr United Kingdom	21	1.0k 1.9×	199 0.7×	306 1.0×	114 0.5×	122 0.7×	32	1.5k
R R de Vries Netherlands	22	806 1.5×	442 1.5×	314 1.0×	113 0.5×	359 2.0×	30	1.9k
Carmelo Luci France	24	1.6k 2.9×	571 1.9×	354 1.2×	64 0.3×	317 1.7×	38	2.4k
Xuchu Que United States	24	616 1.2×	358 1.2×	515 1.7×	51 0.2×	432 2.4×	35	2.0k

Countries citing papers authored by Peter R. Wilker

Since Specialization

Citations

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

Fields of papers citing papers by Peter R. Wilker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter R. Wilker

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

All Works

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16 of 16 papers shown

1.

Liu, Jing, Zhiguang Ren, Hongmei Wang, et al.. (2018). Influenza virus-like particles composed of conserved influenza proteins and GPI-anchored CCL28/GM-CSF fusion proteins enhance protective immunity against homologous and heterologous viruses. International Immunopharmacology. 63. 119–128. 11 indexed citations

2.

Feng, Na, Tiecheng Wang, Peter R. Wilker, et al.. (2016). Fatal canine distemper virus infection of giant pandas in China. Scientific Reports. 6(1). 27518–27518. 80 indexed citations

3.

Yu, Zhijun, Kaihui Cheng, Weiyang Sun, et al.. (2015). A PB1 T296R substitution enhance polymerase activity and confer a virulent phenotype to a 2009 pandemic H1N1 influenza virus in mice. Virology. 486. 180–186. 23 indexed citations

4.

Wilker, Peter R., Jorge M. Dinis, Gabriel J. Starrett, et al.. (2013). Selection on haemagglutinin imposes a bottleneck during mammalian transmission of reassortant H5N1 influenza viruses. Nature Communications. 4(1). 2636–2636. 64 indexed citations

5.

Das, Subash C., Masato Hatta, Peter R. Wilker, et al.. (2012). Nanoemulsion W805EC improves immune responses upon intranasal delivery of an inactivated pandemic H1N1 influenza vaccine. Vaccine. 30(48). 6871–6877. 31 indexed citations

6.

Walsh, Kevin B., John R. Teijaro, Peter R. Wilker, et al.. (2011). Suppression of cytokine storm with a sphingosine analog provides protection against pathogenic influenza virus. Proceedings of the National Academy of Sciences. 108(29). 12018–12023. 195 indexed citations

7.

Walsh, Kevin B., Peter R. Wilker, M. Suresh, et al.. (2011). Pathogenic H1N1 2009 influenza virus-induced pulmonary injury is suppressed by sphingosine analog-mediated inhibition of cytokine storm (49.3). The Journal of Immunology. 186(1_Supplement). 49.3–49.3. 1 indexed citations

8.

Smith, Kirk, Peter R. Wilker, Paul L. Reiter, et al.. (2011). Antibiotic Treatment of Escherichia coli O157 Infection and the Risk of Hemolytic Uremic Syndrome, Minnesota. The Pediatric Infectious Disease Journal. 31(1). 37–41. 110 indexed citations

9.

Kohyama, Masako, Wataru Ise, Brian T. Edelson, et al.. (2008). Role for Spi-C in the development of red pulp macrophages and splenic iron homeostasis. Nature. 457(7227). 318–321. 346 indexed citations

10.

Wilker, Peter R., Masako Kohyama, Michelle M. Sandau, et al.. (2008). Transcription factor Mef2c is required for B cell proliferation and survival after antigen receptor stimulation. Nature Immunology. 9(6). 603–612. 132 indexed citations

11.

Wilker, Peter R., John R. Šedý, Vadim Grigura, Theresa L. Murphy, & Kenneth M. Murphy. (2007). Evidence for carbohydrate recognition and homotypic and heterotypic binding by the TIM family. International Immunology. 19(6). 763–773. 40 indexed citations

12.

Bougie, Daniel W., Peter R. Wilker, & Richard H. Aster. (2006). Patients with quinine-induced immune thrombocytopenia have both “drug-dependent” and “drug-specific” antibodies. Blood. 108(3). 922–927. 77 indexed citations

13.

Bougie, Daniel W., Peter R. Wilker, Brian R. Curtis, et al.. (2002). Acute thrombocytopenia after treatment with tirofiban or eptifibatide is associated with antibodies specific for ligand-occupied GPIIb/IIIa. Blood. 100(6). 2071–2076. 154 indexed citations

14.

Bougie, Daniel W., Peter R. Wilker, Brian R. Curtis, et al.. (2002). Acute thrombocytopenia after treatment with tirofiban or eptifibatide is associated with antibodies specific for ligand-occupied GPIIb/IIIa. Blood. 100(6). 2071–2076. 19 indexed citations

15.

Lord, Raymond S., et al.. (2000). Immune hemolytic anemia caused by sensitivity to a metabolite of etodolac, a nonsteroidal anti‐inflammatory drug. Transfusion. 40(6). 663–668. 16 indexed citations

16.

Wilker, Peter R.. (1980). An Efficient Algorithmic Solution of the Diophantine Equation u 2 + 5υ 2 = m. Mathematics of Computation. 35(152). 1347–1347. 2 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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