Barbara R. Williams

25 total papers · 467 total citations
16 papers, 354 citations indexed

About

Barbara R. Williams is a scholar working on Radiology, Nuclear Medicine and Imaging, Immunology and Molecular Biology. According to data from OpenAlex, Barbara R. Williams has authored 16 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Immunology and 2 papers in Molecular Biology. Recurrent topics in Barbara R. Williams's work include Monoclonal and Polyclonal Antibodies Research (4 papers), T-cell and B-cell Immunology (4 papers) and Connective tissue disorders research (2 papers). Barbara R. Williams is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (4 papers), T-cell and B-cell Immunology (4 papers) and Connective tissue disorders research (2 papers). Barbara R. Williams collaborates with scholars based in United States and United Kingdom. Barbara R. Williams's co-authors include Jean E. Sanders, Reginald A. Clift, E. Donnall Thomas, Brian Schofield, Stephen B. Doty, E W Lamon, Kenneth S. Brown, Roslyn W. Orkin, E W Fuson and Alan Kennedy and has published in prestigious journals such as New England Journal of Medicine, The Journal of Cell Biology and The Journal of Immunology.

In The Last Decade

Barbara R. Williams

16 papers receiving 306 citations

Author Peers

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

Author						Papers	Cites
Barbara R. Williams	128	87	87	69	59	16	354
M. Nakamura	43 0.3×	190 2.2×	28 0.3×	41 0.6×	24 0.4×	21	395
Chengxiang Wu	64 0.5×	158 1.8×	45 0.5×	57 0.8×	31 0.5×	25	386
Ren An	31 0.2×	111 1.3×	23 0.3×	28 0.4×	35 0.6×	14	388
Alice Maniatis	56 0.4×	117 1.3×	111 1.3×	25 0.4×	11 0.2×	14	388
M Teramura	66 0.5×	63 0.7×	228 2.6×	36 0.5×	14 0.2×	20	395
Tina Nilsson	121 0.9×	98 1.1×	35 0.4×	29 0.4×	31 0.5×	17	309
A Hiraoka	34 0.3×	120 1.4×	49 0.6×	22 0.3×	21 0.4×	19	325
H Høyer	28 0.2×	62 0.7×	71 0.8×	77 1.1×	63 1.1×	15	336
Oppenheim Jj	68 0.5×	49 0.6×	39 0.4×	20 0.3×	13 0.2×	18	327
Katalin Olasz	61 0.5×	93 1.1×	22 0.3×	31 0.4×	16 0.3×	21	352

Countries citing papers authored by Barbara R. Williams

Since Specialization

Citations

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

Fields of papers citing papers by Barbara R. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Barbara R. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Barbara R. Williams. A scholar is included among the top collaborators of Barbara R. Williams 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 Barbara R. Williams. Barbara R. Williams 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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