Daniel J. Burdick

2.3k citations
21 papers · 670 · h-index 13

Impact in

Papers in

    • Chemical Synthesis and Analysis 4
    • RNA and protein synthesis mechanisms 3
    • Lipoproteins and Cardiovascular Health 3

Daniel J. Burdick

21 papers receiving 589 citations

Peers

Daniel J. Burdick
Comparison fields: 5 of 72
  • Immunology and Allergy 96
  • Hematology 65
  • Molecular Biology 384
  • Radiology, Nuclear Medicine and Imaging 115
  • Endocrine and Autonomic Systems 26
Replace Martin Schröder with:
Martin Schröder Germany
Mary Pat Beavers United States
Y Uehara Japan
Huawei Qiu United States
Rajasree Golla United States
Nanni Huser United States
Mary Gregoriou United Kingdom
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John T. Miller United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel J. Burdick

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Burdick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel J. Burdick, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel J. Burdick Line = papers co-authored together Daniel J. Burdick links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992146
2 198996
3 201266
4 199563
5 201752
6 199444
7 199442
8 200326
9 199326
10 202016
11 200315
12 201515
13 199713
14 202310
15 200410
16 20208
17 19878
18 19956
19 20234
20 20053

About Daniel J. Burdick

Daniel J. Burdick is a scholar working on Molecular Biology, Surgery, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging and Hematology, having authored 21 papers that have together received 670 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Chemical Synthesis and Analysis (4 papers), Cell Adhesion Molecules Research (4 papers), RNA and protein synthesis mechanisms (3 papers), Peptidase Inhibition and Analysis (3 papers), Lipoproteins and Cardiovascular Health (3 papers) and Hematopoietic Stem Cell Transplantation (2 papers). The work is most often cited by research in Immunology and Allergy (96 citations), Hematology (65 citations), Molecular Biology (384 citations), Radiology, Nuclear Medicine and Imaging (115 citations) and Endocrine and Autonomic Systems (26 citations). Daniel J. Burdick has collaborated with scholars based in United States, Belarus and France. Frequent co-authors include John P. Burnier, Thomas R. Gadek, Charles Eigenbrot, Peter L. Barker, James A. Wells, Paul Carter, Robert S. McDowell, Stuart Bunting, Robin D. Gantzos and T.A. Deisher. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, ACS Chemical Biology, Journal of Medicinal Chemistry, Experimental Hematology and Journal of the American Chemical Society.

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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