Robert N. Barker

716 total citations
9 papers, 551 citations indexed

About

Robert N. Barker is a scholar working on Hematology, Physiology and Immunology. According to data from OpenAlex, Robert N. Barker has authored 9 papers receiving a total of 551 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Hematology, 5 papers in Physiology and 5 papers in Immunology. Recurrent topics in Robert N. Barker's work include Blood groups and transfusion (5 papers), Erythrocyte Function and Pathophysiology (4 papers) and T-cell and B-cell Immunology (3 papers). Robert N. Barker is often cited by papers focused on Blood groups and transfusion (5 papers), Erythrocyte Function and Pathophysiology (4 papers) and T-cell and B-cell Immunology (3 papers). Robert N. Barker collaborates with scholars based in United Kingdom. Robert N. Barker's co-authors include Anthony Seaton, Graham Devereux, Christopher J. Elson, Christopher J. Elson, Neil Williams, Stephen J. Thompson, Lars-Peter Erwig, Wayne Pearce, Geraldo Gileno de Sá Oliveira and Peter M. Lydyard and has published in prestigious journals such as European Journal of Immunology, Clinical & Experimental Allergy and Haematologica.

In The Last Decade

Robert N. Barker

9 papers receiving 531 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Robert N. Barker United Kingdom	8	253	244	138	78	75	9	551
Elif Karakoç-Aydıner Türkiye	18	249 1.0×	445 1.8×	85 0.6×	150 1.9×	183 2.4×	72	900
Ayça Kıykım Türkiye	13	109 0.4×	389 1.6×	58 0.4×	67 0.9×	179 2.4×	71	643
Anette Bohnert Germany	13	144 0.6×	212 0.9×	19 0.1×	182 2.3×	26 0.3×	18	497
Dilek Doğruel Türkiye	12	54 0.2×	78 0.3×	30 0.2×	100 1.3×	44 0.6×	53	366
Ari M. Simckes United States	10	73 0.3×	179 0.7×	95 0.7×	71 0.9×	61 0.8×	16	657
Monique E. Lodewijk Netherlands	13	303 1.2×	167 0.7×	10 0.1×	306 3.9×	25 0.3×	21	621
Y Yoshizawa Japan	9	91 0.4×	56 0.2×	51 0.4×	165 2.1×	11 0.1×	17	385
Vedat Uygun Türkiye	13	65 0.3×	113 0.5×	174 1.3×	72 0.9×	61 0.8×	57	486
Taro Okayama Japan	11	169 0.7×	101 0.4×	88 0.6×	59 0.8×	89 1.2×	24	490
Neil Haldar United Kingdom	9	78 0.3×	110 0.5×	26 0.2×	50 0.6×	65 0.9×	12	504

Countries citing papers authored by Robert N. Barker

Since Specialization

Citations

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

Fields of papers citing papers by Robert N. Barker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert N. Barker. 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 Robert N. Barker. The network helps show where Robert N. Barker may publish in the future.

Co-authorship network of co-authors of Robert N. Barker

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

All Works

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9 of 9 papers shown

1.

Hall, Andrew M., et al.. (2014). Combination peptide immunotherapy suppresses antibody and helper T-cell responses to the RhD protein in HLA-transgenic mice. Haematologica. 99(3). 588–596. 7 indexed citations

2.

Hall, Andrew M., et al.. (2012). Production of the effector cytokine interleukin-17, rather than interferon- , is more strongly associated with autoimmune hemolytic anemia. Haematologica. 97(10). 1494–1500. 18 indexed citations

3.

Devereux, Graham, Robert N. Barker, & Anthony Seaton. (2002). Antenatal determinants of neonatal immune responses to allergens. Clinical & Experimental Allergy. 32(1). 43–50. 212 indexed citations

4.

Barker, Robert N., et al.. (1999). Differential Effects of Necrotic or Apoptotic Cell Uptake on Antigen Presentation by Macrophages. Pathobiology. 67(5-6). 302–305. 57 indexed citations

5.

Barker, Robert N., et al.. (1999). Serial Changes in the Galactosylation of Autoantibodies and Serum IgG in Autoimmune Haemolytic Anaemia. Autoimmunity. 31(2). 103–108. 6 indexed citations

6.

Barker, Robert N., et al.. (1996). Autoreactive T cell specificity in autoimmune hemolytic anemia of the NZB mouse. European Journal of Immunology. 26(1). 136–141. 33 indexed citations

7.

Elson, Christopher J., Robert N. Barker, Stephen J. Thompson, & Neil Williams. (1995). Immunologically ignorant autoreactive T cells, epitope spreading and repertoire limitation. Immunology Today. 16(2). 71–76. 118 indexed citations

8.

Barker, Robert N. & Christopher J. Elson. (1994). Multiple self epitopes on the Rhesus polypeptides stimulate immunologically ignorant human T cells in vitro. European Journal of Immunology. 24(7). 1578–1582. 60 indexed citations

9.

Barker, Robert N., Geraldo Gileno de Sá Oliveira, Christopher J. Elson, & Peter M. Lydyard. (1993). Pathogenic autoantibodies in the NZB mouse are specific for erythrocyte Band 3 protein. European Journal of Immunology. 23(7). 1723–1726. 40 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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