David P. Barr

59 papers receiving 3.4k citations

David P. Barr's Hit Papers

Protein-lipid relationships in human plasma 1951 · 488 citations
4880+25+50Years since publication100200300400

Peers

David P. Barr
Comparison fields: 5 of 166
  • Biophysics 242
  • Endocrinology, Diabetes and Metabolism 655
  • Biotechnology 267
  • Pollution 344
  • Cancer Research 277
Replace John A. Timbrell with:
John A. Timbrell United Kingdom
Jen‐Fu Chiu Hong Kong
Haïm Tapiero France
R. Preußmann Germany
Raymond W. Nims United States
Phyllis A. Dennery United States
Bruce R. Pitt United States
Danyelle M. Townsend United States
Michaël Thomas United States
Yusuke Hiraku Japan
David P. Barr relative to John A. Timbrell United Kingdom John A. Timbrell's profile →
Citations per field
00.5×3.7×
John A. Timbrell · 1×
Citations per year

Countries citing papers authored by David P. Barr

Since Specialization
Citations

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

Fields of papers citing papers by David P. Barr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David P. Barr, 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 David P. Barr Line = papers co-authored together David P. Barr links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Protein-lipid relationships in human plasma
Hit paper breakdown →
1951488
2 1994376
3 2010276
4 1951268
5 1953124
6 1996120
7 1953111
8 1956110
9 1996108
10 1995105
11 1955103
12 1994100
13 202291
14 195388
15 199787
16 195581
17 199981
18 199477
19 199875
20 197573

About David P. Barr

David P. Barr is a scholar working on Plant Science, Biophysics, Surgery, Organic Chemistry and Health, Toxicology and Mutagenesis, having authored 62 papers that have together received 3.9k indexed citations. Recurring topics across this work include Enzyme-mediated dye degradation (12 papers), Electron Spin Resonance Studies (11 papers), Environmental Toxicology and Ecotoxicology (3 papers), Burn Injury Management and Outcomes (3 papers), Biochemical and biochemical processes (3 papers), Hemoglobin structure and function (3 papers), Photosynthetic Processes and Mechanisms (3 papers) and Liver Disease Diagnosis and Treatment (3 papers). The work is most often cited by research in Biophysics (242 citations), Endocrinology, Diabetes and Metabolism (655 citations), Biotechnology (267 citations), Pollution (344 citations) and Cancer Research (277 citations). David P. Barr has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Ella M. Russ, Steven D. Aust, Howard A. Eder, Ronald P. Mason, Ralph T. Weber, Lev Bromberg, Gareth R. Eaton, Sandra S. Eaton, Michael R. Gunther and Leesa J. Deterding. Their work appears in journals such as Archives of Biochemistry and Biophysics, Journal of Biological Chemistry, The American Journal of Medicine, Journal of Clinical Investigation and Circulation.

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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