Daniel M. Williams

30 total papers · 1.5k total citations
14 papers, 516 citations indexed

About

Daniel M. Williams is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Cell Biology. According to data from OpenAlex, Daniel M. Williams has authored 14 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 3 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Cell Biology. Recurrent topics in Daniel M. Williams's work include Inflammasome and immune disorders (5 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Heme Oxygenase-1 and Carbon Monoxide (3 papers). Daniel M. Williams is often cited by papers focused on Inflammasome and immune disorders (5 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Heme Oxygenase-1 and Carbon Monoxide (3 papers). Daniel M. Williams collaborates with scholars based in United States, United Kingdom and Japan. Daniel M. Williams's co-authors include Philip A. Cole, M. O. Aksoy, D.J. Hartshorne, Dongxia Wang, Attila Szűcs, Valentina Lo Sardo, Pietro Paolo Sanna, Joel Blanchard, Kristin K. Baldwin and Kevin Eade and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Accounts of Chemical Research.

In The Last Decade

Daniel M. Williams

14 papers receiving 491 citations

Author Peers

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

Author Last Decade Papers Cites
Daniel M. Williams 390 86 81 75 57 14 516
Ying Li 272 0.7× 138 1.6× 72 0.9× 42 0.6× 56 1.0× 16 453
Gerda E. Mark 277 0.7× 184 2.1× 59 0.7× 137 1.8× 55 1.0× 12 563
Nellie Kalcheva 256 0.7× 66 0.8× 114 1.4× 44 0.6× 40 0.7× 14 503
Biswarathan Ramani 419 1.1× 139 1.6× 54 0.7× 54 0.7× 41 0.7× 10 540
Robert Pascal Requardt 301 0.8× 150 1.7× 95 1.2× 46 0.6× 50 0.9× 15 610
Yiwen Li 394 1.0× 91 1.1× 27 0.3× 55 0.7× 26 0.5× 16 554
Olga Zinchuk 306 0.8× 51 0.6× 72 0.9× 19 0.3× 54 0.9× 8 568
Marisol Montolio 412 1.1× 190 2.2× 51 0.6× 35 0.5× 35 0.6× 18 545
Thierry Métayé 352 0.9× 118 1.4× 80 1.0× 22 0.3× 54 0.9× 22 617
F. Lang 382 1.0× 133 1.5× 74 0.9× 48 0.6× 74 1.3× 11 562

Countries citing papers authored by Daniel M. Williams

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel M. Williams

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