T. M. Dexter

113 total papers · 7.0k total citations
87 papers, 5.8k citations indexed

About

T. M. Dexter is a scholar working on Hematology, Molecular Biology and Physiology. According to data from OpenAlex, T. M. Dexter has authored 87 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Hematology, 23 papers in Molecular Biology and 17 papers in Physiology. Recurrent topics in T. M. Dexter's work include Hematopoietic Stem Cell Transplantation (28 papers), Mesenchymal stem cell research (11 papers) and Erythrocyte Function and Pathophysiology (11 papers). T. M. Dexter is often cited by papers focused on Hematopoietic Stem Cell Transplantation (28 papers), Mesenchymal stem cell research (11 papers) and Erythrocyte Function and Pathophysiology (11 papers). T. M. Dexter collaborates with scholars based in United Kingdom, United States and Japan. T. M. Dexter's co-authors include Elaine Spooncer, J. M. Garland, Dale R. Taylor, Christopher A. Smith, Gwyn T. Williams, Edward M. Scolnick, D Metcalf, D Scott, Anthony D. Whetton and L. G. Lajtha and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

T. M. Dexter

85 papers receiving 5.5k citations

Hit Papers

Haemopoietic colony stimu... 1980 2026 1995 2010 1990 1988 1980 250 500 750

Author Peers

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

Author Last Decade Papers Cites
T. M. Dexter 2.3k 2.1k 1.9k 1.0k 923 87 5.8k
Kohichiro Tsuji 2.2k 1.0× 2.0k 1.0× 2.4k 1.3× 1.4k 1.3× 1.3k 1.4× 112 6.3k
T. M. Dexter 2.3k 1.0× 2.6k 1.2× 1.8k 0.9× 1.5k 1.5× 1.2k 1.3× 101 6.3k
Laure Coulombel 1.9k 0.8× 2.5k 1.2× 1.5k 0.8× 715 0.7× 1.1k 1.2× 127 5.3k
D. Robert Sutherland 2.5k 1.1× 3.1k 1.5× 2.3k 1.2× 1.5k 1.4× 1.2k 1.3× 97 7.3k
Jon Frampton 3.0k 1.3× 1.6k 0.8× 2.3k 1.2× 721 0.7× 555 0.6× 100 7.4k
KM Zsebo 1.7k 0.7× 2.3k 1.1× 2.6k 1.4× 971 0.9× 956 1.0× 82 5.6k
Donald C. Foster 2.2k 0.9× 3.8k 1.8× 1.4k 0.8× 741 0.7× 1.3k 1.5× 77 8.2k
Reuben Kapur 2.8k 1.2× 1.3k 0.6× 2.4k 1.3× 925 0.9× 727 0.8× 171 6.0k
Elaine Spooncer 2.4k 1.1× 1.4k 0.7× 1.3k 0.7× 790 0.8× 563 0.6× 77 4.7k
G. S. Hodgson 1.6k 0.7× 1.6k 0.8× 2.6k 1.4× 1.3k 1.2× 751 0.8× 107 5.8k

Countries citing papers authored by T. M. Dexter

Since Specialization
Citations

This map shows the geographic impact of T. M. Dexter'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 T. M. Dexter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. M. Dexter more than expected).

Fields of papers citing papers by T. M. Dexter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. M. Dexter

This figure shows the co-authorship network connecting the top 25 collaborators of T. M. Dexter. A scholar is included among the top collaborators of T. M. Dexter 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 T. M. Dexter. T. M. Dexter 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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