Brian Naiman

1.9k total citations
16 papers, 1.0k citations indexed

About

Brian Naiman is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Brian Naiman has authored 16 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 4 papers in Molecular Biology and 3 papers in Oncology. Recurrent topics in Brian Naiman's work include Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (5 papers) and Leptospirosis research and findings (2 papers). Brian Naiman is often cited by papers focused on Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (5 papers) and Leptospirosis research and findings (2 papers). Brian Naiman collaborates with scholars based in United States, Sweden and United Kingdom. Brian Naiman's co-authors include Cynthia L. Baldwin, Richard L. Zuerner, Carole A. Bolin, David P. Alt, Per‐Johan Jakobsson, Marsha L. Roach, Sipra Saha, Thomas J. Carty, Jeffrey L. Stock and Karamjeet Pandher and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Immunology and PLoS ONE.

In The Last Decade

Brian Naiman

16 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Brian Naiman United States	11	314	305	298	176	129	16	1.0k
Dae Yong Kim South Korea	22	66 0.2×	471 1.5×	212 0.7×	107 0.6×	133 1.0×	53	1.4k
David R. Webb United States	15	108 0.3×	220 0.7×	433 1.5×	75 0.4×	74 0.6×	38	822
Liana Verinaud Brazil	21	63 0.2×	311 1.0×	362 1.2×	45 0.3×	71 0.6×	61	1.1k
Yonghong Zhu China	23	126 0.4×	838 2.7×	132 0.4×	20 0.1×	204 1.6×	43	1.5k
Tamara Tanos Argentina	18	32 0.1×	796 2.6×	205 0.7×	153 0.9×	157 1.2×	23	1.5k
Michele M. Barsante Brazil	15	44 0.1×	225 0.7×	359 1.2×	195 1.1×	19 0.1×	18	904
G P Linette United States	10	39 0.1×	484 1.6×	158 0.5×	154 0.9×	37 0.3×	15	916
Jianping Pan China	20	61 0.2×	480 1.6×	448 1.5×	23 0.1×	65 0.5×	43	1.2k
Barbara Magi Italy	20	42 0.1×	638 2.1×	187 0.6×	49 0.3×	85 0.7×	37	1.5k
Pedro Ostoa‐Saloma Mexico	14	24 0.1×	328 1.1×	206 0.7×	219 1.2×	56 0.4×	45	971

Countries citing papers authored by Brian Naiman

Since Specialization

Citations

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

Fields of papers citing papers by Brian Naiman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Naiman

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Naiman. A scholar is included among the top collaborators of Brian Naiman 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 Brian Naiman. Brian Naiman 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

Malhotra, Deepali, Eleanor Clancy‐Thompson, Bilal Omar, et al.. (2022). 469 Preclinical studies support clinical development of AZD2936, a monovalent bispecific humanized antibody targeting PD-1 and TIGIT. Regular and Young Investigator Award Abstracts. A489–A489. 5 indexed citations

Vousden, Katherine A., T. Lundqvist, Bojana Popovic, et al.. (2019). Discovery and characterisation of an antibody that selectively modulates the inhibitory activity of plasminogen activator inhibitor-1. Scientific Reports. 9(1). 1605–1605. 24 indexed citations

Karnell, Jodi L., Qiming Wang, Shu Wang, et al.. (2017). Autoimmune manifestations in aged mice arise from early-life immune dysregulation. The Journal of Immunology. 198(Supplement_1). 54.1–54.1. 1 indexed citations

Wang, Shu, Jingya Wang, Varsha Kumar, et al.. (2017). Role and Regulation of CD11chi T-bet+ B cells in SLE. The Journal of Immunology. 198(Supplement_1). 54.4–54.4. 1 indexed citations

Wang, Jingya, Jodi L. Karnell, Qiming Wang, et al.. (2016). Autoimmune manifestations in aged mice arise from early-life immune dysregulation. Science Translational Medicine. 8(361). 361ra137–361ra137. 39 indexed citations

Le, Catherine T., Christopher Morehouse, Brian Naiman, et al.. (2015). Synergistic Actions of Blocking Angiopoietin-2 and Tumor Necrosis Factor-α in Suppressing Remodeling of Blood Vessels and Lymphatics in Airway Inflammation. American Journal Of Pathology. 185(11). 2949–2968. 23 indexed citations

Chen, Bo, Allison L. Miller, Marlon C. Rebelatto, et al.. (2015). S100A9 Induced Inflammatory Responses Are Mediated by Distinct Damage Associated Molecular Patterns (DAMP) Receptors In Vitro and In Vivo. PLoS ONE. 10(2). e0115828–e0115828. 95 indexed citations

An, Ling–Ling, Payal Mehta, Linda Xu, et al.. (2014). Complement C5a potentiates uric acid crystal‐induced IL‐1β production. European Journal of Immunology. 44(12). 3669–3679. 55 indexed citations

Krausz, Sarah, Samuel García, Carmen A. Ambarus, et al.. (2012). Angiopoietin-2 promotes inflammatory activation of human macrophages and is essential for murine experimental arthritis. Annals of the Rheumatic Diseases. 71(8). 1402–1410. 38 indexed citations

10.

Chen, Bo, Ricardo Cibotti, Brian Naiman, et al.. (2008). Genomic-Based High Throughput Screening Identifies Small Molecules That Differentially Inhibit the Antiviral and Immunomodulatory Effects of IFN-α. Molecular Medicine. 14(7-8). 374–382. 3 indexed citations

11.

Trebino, Catherine E., Jeffrey L. Stock, Colleen P. Gibbons, et al.. (2003). Impaired inflammatory and pain responses in mice lacking an inducible prostaglandin E synthase. Proceedings of the National Academy of Sciences. 100(15). 9044–9049. 471 indexed citations

12.

Baldwin, Cynthia L., Brian Naiman, Rachel A. Brown, et al.. (2002). Activation of bovine peripheral blood γδ T cells for cell division and IFN-γ production. Veterinary Immunology and Immunopathology. 87(3-4). 251–259. 42 indexed citations

13.

Naiman, Brian, et al.. (2002). Immunological characterization of a γδ T‐cell stimulatory ligand on autologous monocytes. Immunology. 105(2). 181–189. 17 indexed citations

14.

Naiman, Brian, Seth L. Blumerman, David P. Alt, et al.. (2002). Evaluation of Type 1 Immune Response in Naive and Vaccinated Animals following Challenge withLeptospira borgpeterseniiSerovar Hardjo: Involvement of WC1⁺γδ and CD4 T Cells. Infection and Immunity. 70(11). 6147–6157. 80 indexed citations

15.

Blumerman, Seth L., et al.. (2002). Expression of the bovine high affinity IL-12 receptor β2. Veterinary Immunology and Immunopathology. 84(3-4). 127–142. 8 indexed citations

16.

Naiman, Brian, David P. Alt, Carole A. Bolin, Richard L. Zuerner, & Cynthia L. Baldwin. (2001). Protective KilledLeptospira borgpeterseniiVaccine Induces Potent Th1 Immunity Comprising Responses by CD4 and γδ T Lymphocytes. Infection and Immunity. 69(12). 7550–7558. 147 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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