David M. Spalding

46 total papers · 989 total citations
29 papers, 731 citations indexed

About

David M. Spalding is a scholar working on Immunology, Experimental and Cognitive Psychology and Molecular Biology. According to data from OpenAlex, David M. Spalding has authored 29 papers receiving a total of 731 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 6 papers in Experimental and Cognitive Psychology and 4 papers in Molecular Biology. Recurrent topics in David M. Spalding's work include T-cell and B-cell Immunology (12 papers), Immunotherapy and Immune Responses (10 papers) and Immune Cell Function and Interaction (6 papers). David M. Spalding is often cited by papers focused on T-cell and B-cell Immunology (12 papers), Immunotherapy and Immune Responses (10 papers) and Immune Cell Function and Interaction (6 papers). David M. Spalding collaborates with scholars based in United States, United Kingdom and Germany. David M. Spalding's co-authors include William J. Koopman, Jerry R. McGhee, I. Pilowsky, John H. Eldridge, Ralph M. Steinman, Louise A. Brown, Michael J. Wannemuehler, Suzanne M. Michalek, Alan J. Gow and Michelle C. Carlson and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and The Journal of Experimental Medicine.

In The Last Decade

David M. Spalding

26 papers receiving 688 citations

Author Peers

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

Author						Papers	Cites
David M. Spalding	403	118	87	43	42	29	731
Macfarlane Burnet	212 0.5×	149 1.3×	72 0.8×	103 2.4×	30 0.7×	32	691
Shoki Yano	155 0.4×	155 1.3×	19 0.2×	91 2.1×	21 0.5×	37	740
Constantin Fesel	339 0.8×	139 1.2×	66 0.8×	76 1.8×	76 1.8×	27	895
Viviana Ferlazzo	329 0.8×	153 1.3×	26 0.3×	119 2.8×	40 1.0×	23	903
Elizabeth M. Andrew	386 1.0×	108 0.9×	52 0.6×	85 2.0×	39 0.9×	35	817
Jacqueline McCormack	235 0.6×	106 0.9×	46 0.5×	103 2.4×	48 1.1×	30	864
Amit Arya	343 0.9×	73 0.6×	42 0.5×	52 1.2×	8 0.2×	56	873
Frank Larsen	290 0.7×	133 1.1×	28 0.3×	65 1.5×	38 0.9×	18	861
M.J. de Vries	240 0.6×	155 1.3×	92 1.1×	86 2.0×	16 0.4×	35	892
SR Mehta	219 0.5×	126 1.1×	88 1.0×	50 1.2×	11 0.3×	40	675

Countries citing papers authored by David M. Spalding

Since Specialization

Citations

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

Fields of papers citing papers by David M. Spalding

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David M. Spalding. 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 David M. Spalding. The network helps show where David M. Spalding may publish in the future.

Co-authorship network of co-authors of David M. Spalding

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

All Works

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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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