Wayne D. Comper

6.5k total citations · 1 hit paper
139 papers, 5.1k citations indexed

About

Wayne D. Comper is a scholar working on Nephrology, Molecular Biology and Cell Biology. According to data from OpenAlex, Wayne D. Comper has authored 139 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Nephrology, 44 papers in Molecular Biology and 24 papers in Cell Biology. Recurrent topics in Wayne D. Comper's work include Chronic Kidney Disease and Diabetes (52 papers), Protein Interaction Studies and Fluorescence Analysis (34 papers) and Renal Diseases and Glomerulopathies (26 papers). Wayne D. Comper is often cited by papers focused on Chronic Kidney Disease and Diabetes (52 papers), Protein Interaction Studies and Fluorescence Analysis (34 papers) and Renal Diseases and Glomerulopathies (26 papers). Wayne D. Comper collaborates with scholars based in Australia, United States and Sweden. Wayne D. Comper's co-authors include Tanya M. Osicka, T.C. Laurent, Leileata M. Russo, George Jerums, Arthur Veis, Stuart A. Newman, B. N. Preston, Lynette M. Pratt, Dennis Brown and Bruce A. Molitoris and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Wayne D. Comper

137 papers receiving 4.9k citations

Hit Papers

Physiological function of connective tissue polysaccharides. 1978 2026 1994 2010 1978 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wayne D. Comper Australia 37 2.2k 1.6k 863 403 393 139 5.1k
Masahiro Ikeda Japan 38 698 0.3× 2.4k 1.5× 346 0.4× 467 1.2× 256 0.7× 230 5.2k
Seymour Rosen United States 49 4.1k 1.9× 2.4k 1.5× 489 0.6× 592 1.5× 521 1.3× 197 9.7k
Tomoki Kosugi Japan 32 956 0.4× 993 0.6× 253 0.3× 291 0.7× 376 1.0× 87 3.8k
Gerhard A. Müller Germany 52 2.9k 1.3× 3.5k 2.3× 406 0.5× 867 2.2× 739 1.9× 302 10.5k
Matthias Meier Germany 38 807 0.4× 1.7k 1.1× 161 0.2× 568 1.4× 173 0.4× 136 4.4k
C. C. Michel United Kingdom 38 679 0.3× 1.3k 0.8× 880 1.0× 593 1.5× 123 0.3× 99 5.4k
A.R. Bradwell United Kingdom 53 1.1k 0.5× 5.4k 3.5× 254 0.3× 197 0.5× 656 1.7× 247 10.2k
Daisuke Suzuki Japan 36 768 0.3× 868 0.6× 189 0.2× 187 0.5× 320 0.8× 246 5.1k
Simon J. Atkinson United States 37 396 0.2× 2.4k 1.5× 1.4k 1.6× 393 1.0× 179 0.5× 73 5.5k
Teruo Watanabe Japan 45 583 0.3× 1.8k 1.1× 209 0.2× 912 2.3× 272 0.7× 171 6.2k

Countries citing papers authored by Wayne D. Comper

Since Specialization
Citations

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

Fields of papers citing papers by Wayne D. Comper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wayne D. Comper. 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 Wayne D. Comper. The network helps show where Wayne D. Comper may publish in the future.

Co-authorship network of co-authors of Wayne D. Comper

This figure shows the co-authorship network connecting the top 25 collaborators of Wayne D. Comper. A scholar is included among the top collaborators of Wayne D. Comper 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 Wayne D. Comper. Wayne D. Comper 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.
Maesaka, John K., Louis J. Imbriano, Aaron Pinkhasov, et al.. (2020). Identification of a Novel Natriuretic Protein in Patients With Cerebral-Renal Salt Wasting—Implications for Enhanced Diagnosis. The American Journal of the Medical Sciences. 361(2). 261–268. 9 indexed citations
2.
3.
Osicka, Tanya M., et al.. (2007). Albuminuria: Its Importance in Disease Detection. Laboratory Medicine. 38(1). 35–38. 11 indexed citations
4.
Russo, Leileata M., Ruben M. Sandoval, Dennis Brown, Bruce A. Molitoris, & Wayne D. Comper. (2007). Response to ‘On the origin of albuminuria’. Kidney International. 72(11). 1409–1410. 1 indexed citations
5.
Russo, Leileata M., Ruben M. Sandoval, Mary McKee, et al.. (2007). The normal kidney filters nephrotic levels of albumin retrieved by proximal tubule cells: Retrieval is disrupted in nephrotic states. Kidney International. 71(6). 504–513. 294 indexed citations
6.
Comper, Wayne D. & Tanya M. Osicka. (2004). Albumin-like material in urine. Kidney International. 66(92). S65–S66. 9 indexed citations
7.
Forbes, Josephine M., et al.. (2003). Reversible Angiotensin II-Mediated Albuminuria in Rat Kidneys Is Dynamically Associated with Cytoskeletal Organization. Nephron Physiology. 93(2). p51–p60. 14 indexed citations
8.
Pratt, Lynette M., et al.. (2003). Anomalous fractional clearance of negatively charged Ficoll relative to uncharged Ficoll. American Journal of Physiology-Renal Physiology. 285(6). F1118–F1124. 38 indexed citations
9.
Eppel, Gabriela A., et al.. (2001). Immuno-unreactive albumin excretion increases in streptozotocin diabetic rats. American Journal of Kidney Diseases. 38(1). 144–152. 27 indexed citations
10.
Osicka, Tanya M., et al.. (2001). Ramipril and aminoguanidine restore renal lysosomal processing in streptozotocin diabetic rats. Diabetologia. 44(2). 230–236. 36 indexed citations
11.
Eppel, Gabriela A., K Takazoe, David J. Nikolic‐Paterson, et al.. (2000). Characteristics of albumin processing during renal passage in Anti-Thy1 and anti–glomerular basement membrane glomerulonephritis. American Journal of Kidney Diseases. 35(3). 418–426. 14 indexed citations
12.
Comper, Wayne D., Gabriela A. Eppel, Tanya M. Osicka, Eric Glasgow, & Paula Jablonski. (2000). Reply from the authors. Kidney International. 57(3). 1208–1209. 1 indexed citations
13.
Comper, Wayne D., et al.. (1997). Changes in Sulfated Macromolecules Produced In Vivo During Normal and Indomethacin-Delayed Ulcer Healing in Rats. Digestive Diseases and Sciences. 42(8). 1755–1764. 3 indexed citations
14.
Burne, Melissa J., et al.. (1996). Glomerular Processing of Dextran Sulfate during Transcapillary Transport. Archives of Biochemistry and Biophysics. 332(2). 205–212. 34 indexed citations
15.
Comper, Wayne D., et al.. (1996). A codiffusing system as a novel model for capillary wall charge selecivity. Biophysical Chemistry. 62(1-3). 73–80. 14 indexed citations
16.
Comper, Wayne D., et al.. (1995). Uptake of dextran sulphate by glomerular intracellular vesicles during kidney ultrafiltration. Kidney International. 47(3). 945–950. 21 indexed citations
17.
Comper, Wayne D., et al.. (1993). Anionic charge concentration of rat kidney glomeruli and glomerular basement membrane. Biochemical Journal. 289(3). 647–652. 34 indexed citations
18.
Williams, Roderick & Wayne D. Comper. (1990). Osmotic flow caused by polyelectrolytes. Biophysical Chemistry. 36(3). 223–234. 18 indexed citations
19.
Comper, Wayne D., et al.. (1988). Oriented Fibrillogenesis of Collagenin vitroBy Ordered Convection. Connective Tissue Research. 17(1). 33–41. 7 indexed citations
20.
Comper, Wayne D.. (1981). Heparin (and related polysaccharides) : structural and functional properties. 5 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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