David J. Burns

1.3k total citations
39 papers, 937 citations indexed

About

David J. Burns is a scholar working on Sociology and Political Science, Education and Molecular Biology. According to data from OpenAlex, David J. Burns has authored 39 papers receiving a total of 937 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Sociology and Political Science, 7 papers in Education and 6 papers in Molecular Biology. Recurrent topics in David J. Burns's work include HER2/EGFR in Cancer Research (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and Nonprofit Sector and Volunteering (4 papers). David J. Burns is often cited by papers focused on HER2/EGFR in Cancer Research (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and Nonprofit Sector and Volunteering (4 papers). David J. Burns collaborates with scholars based in United States, United Kingdom and Switzerland. David J. Burns's co-authors include Chris Manolis, Mark Toncar, Cynthia Anderson, Ravi Chinta, Rashmi Assudani, Jane S. Reid, Usha Warrior, Jonathan Kent, Linda C. McPhail and Susan Sergeant and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

David J. Burns

37 papers receiving 850 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David J. Burns United States 15 201 181 173 152 142 39 937
Janice S. Miller United States 19 108 0.5× 126 0.7× 195 1.1× 343 2.3× 50 0.4× 33 1.8k
Lin Lü China 25 682 3.4× 235 1.3× 243 1.4× 226 1.5× 16 0.1× 152 2.9k
Mei-Jung Wang Taiwan 16 324 1.6× 107 0.6× 118 0.7× 28 0.2× 47 0.3× 35 860
David S. Knight United States 22 231 1.1× 547 3.0× 149 0.9× 90 0.6× 11 0.1× 106 1.6k
Yoon-Joo Lee United States 18 88 0.4× 84 0.5× 333 1.9× 55 0.4× 258 1.8× 105 1.0k
Simon Wong Hong Kong 15 537 2.7× 77 0.4× 368 2.1× 361 2.4× 428 3.0× 35 1.8k
Seong-Yeon Park South Korea 12 395 2.0× 59 0.3× 176 1.0× 236 1.6× 401 2.8× 52 1.3k
Anna Kim South Korea 18 252 1.3× 41 0.2× 127 0.7× 76 0.5× 59 0.4× 109 1.6k
Bo Shao China 16 78 0.4× 53 0.3× 232 1.3× 295 1.9× 48 0.3× 46 946
Laura Bradley United Kingdom 12 81 0.4× 44 0.2× 224 1.3× 82 0.5× 63 0.4× 48 1.2k

Countries citing papers authored by David J. Burns

Since Specialization
Citations

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

Fields of papers citing papers by David J. Burns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David J. Burns

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

All Works

20 of 20 papers shown
1.
Gomm, Andrew, et al.. (2025). Biotransformations at Syngenta: A Focused Perspective on Metabolites and Natural Products. CHIMIA International Journal for Chemistry. 79(5). 339–343.
2.
MacNeil, Ian A., et al.. (2022). Functional signaling test identifies HER2 negative breast cancer patients who may benefit from c-Met and pan-HER combination therapy. Cell Communication and Signaling. 20(1). 4–4. 2 indexed citations
3.
Burns, David J., et al.. (2020). PANEL: Are Students Our Customers? Perils and Pitfalls of Students as Customers. 1. 1 indexed citations
4.
Burns, David J., Benjamin E. Rich, Ian A. MacNeil, et al.. (2017). Development of a test that measures real-time HER2 signaling function in live breast cancer cell lines and primary cells. BMC Cancer. 17(1). 199–199. 14 indexed citations
5.
6.
Burns, David J. & Debra K. Mooney. (2012). Facilitating Integrating Mission Into the classroom: Xavier’s Mission Academy. Exhibit - A Showcase of Scholarship, Creativity and Preservation Provided by Xavier University Library (Xavier University).
7.
Assudani, Rashmi, Ravi Chinta, Chris Manolis, & David J. Burns. (2011). The Effect of Pedagogy on Students' Perceptions of the Importance of Ethics and Social Responsibility in Business Firms. Ethics & Behavior. 21(2). 103–117. 10 indexed citations
8.
Manolis, Chris & David J. Burns. (2011). Attitudes toward academic service learning semesters: A comparison of business students with non-business students. SHILAP Revista de lepidopterología. 8 indexed citations
9.
Burns, David J., et al.. (2008). The Effect of Gender on the Motivation of Members of Generation Y College Students to Volunteer. Journal of Nonprofit & Public Sector Marketing. 19(1). 99–118. 57 indexed citations
10.
Burns, David J., Ravi Chinta, Vishal Kashyap, Chris Manolis, & Amit Sen. (2008). Hospital Care and Capacity in the Tri-State Region of Indiana, Kentucky, and Ohio: Analysis and Insights. Health Marketing Quarterly. 25(3). 254–269. 4 indexed citations
11.
Burns, David J., et al.. (2005). Volunteering: A Comparison of the Motivations of Collegiate Students Attending Different Types of Institutions. 23(4). 31. 11 indexed citations
12.
Pratt, Steven, Peter J. Dandliker, Xiaoling Xuei, et al.. (2004). A Strategy for Discovery of Novel Broad-Spectrum Antibacterials Using a High-Throughput Streptococcus pneumoniae Transcription/Translation Screen. SLAS DISCOVERY. 9(1). 3–11. 22 indexed citations
13.
Wilkins, Julie A., James L. Kofron, Yong Jia, et al.. (2004). Utilization of Microarrayed Compound Screening (μARCS) to Identify Inhibitors of p56lck Tyrosine Kinase. SLAS DISCOVERY. 9(1). 12–21. 5 indexed citations
14.
Warrior, Usha, Evelyn McKeegan, Linda Traphagen, et al.. (2003). Identification and Characterization of Novel Antagonists of the CCR3 Receptor. SLAS DISCOVERY. 8(3). 324–331. 11 indexed citations
15.
Middleton, Tim, Debra Montgomery, Hock Ben Lim, et al.. (2002). Microarray Compound Screening (μARCS) to Identify Inhibitors of HIV Integrase. SLAS DISCOVERY. 7(3). 259–266. 24 indexed citations
16.
Warrior, Usha, Yihong Fan, Julie A. Wilkins, et al.. (2000). Application of QuantiGene™ Nucleic Acid Quantification Technology for High Throughput Screening. SLAS DISCOVERY. 5(5). 343–351. 22 indexed citations
17.
Warrior, Usha, X. Grace Chiou, Michael P. Sheets, et al.. (1999). Development of a p38 Kinase Binding Assay for High Throughput Screening. SLAS DISCOVERY. 4(3). 129–135. 7 indexed citations
18.
Kent, Jonathan, Susan Sergeant, David J. Burns, & Linda C. McPhail. (1996). Identification and regulation of protein kinase C-delta in human neutrophils. The Journal of Immunology. 157(10). 4641–4647. 81 indexed citations
19.
Sista, Prakash, et al.. (1994). A cell-based reporter assay for the identification of protein kinase C activators and inhibitors. Molecular and Cellular Biochemistry. 141(2). 129–134. 8 indexed citations
20.
Burns, David J.. (1988). The effects of uniqueness seeking and sensation seeking upon innovative behavior and the adoption process. Medical Entomology and Zoology. 6 indexed citations

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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