Ray Fernando

660 total citations
18 papers, 545 citations indexed

About

Ray Fernando is a scholar working on Immunology, Surgery and Nephrology. According to data from OpenAlex, Ray Fernando has authored 18 papers receiving a total of 545 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 5 papers in Surgery and 5 papers in Nephrology. Recurrent topics in Ray Fernando's work include Atherosclerosis and Cardiovascular Diseases (5 papers), Dialysis and Renal Disease Management (3 papers) and Cholesterol and Lipid Metabolism (3 papers). Ray Fernando is often cited by papers focused on Atherosclerosis and Cardiovascular Diseases (5 papers), Dialysis and Renal Disease Management (3 papers) and Cholesterol and Lipid Metabolism (3 papers). Ray Fernando collaborates with scholars based in United Kingdom, China and Greece. Ray Fernando's co-authors include Zac Varghese, Stephen H. Powis, David C. Wheeler, John F. Moorhead, Xiong Z. Ruan, Hang Li, J.F. Moorhead, J F Moorhead, Z. Varghese and P. Sweny and has published in prestigious journals such as Kidney International, Journal of Clinical Pathology and Clinica Chimica Acta.

In The Last Decade

Ray Fernando

18 papers receiving 533 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ray Fernando United Kingdom 10 153 150 148 100 89 18 545
J.L. Paul France 11 100 0.7× 113 0.8× 182 1.2× 82 0.8× 93 1.0× 18 570
Megan E. Rudock United States 9 182 1.2× 174 1.2× 72 0.5× 94 0.9× 89 1.0× 10 572
Chuchun L. Chang United States 14 187 1.2× 107 0.7× 126 0.9× 92 0.9× 15 0.2× 25 502
Tatsuto Notsu Japan 16 131 0.9× 185 1.2× 87 0.6× 105 1.1× 14 0.2× 19 628
Josefa Pete Australia 7 81 0.5× 329 2.2× 82 0.6× 118 1.2× 186 2.1× 9 891
Jaya Bollineni United States 13 94 0.6× 224 1.5× 255 1.7× 50 0.5× 74 0.8× 15 665
Allison B. Lehtinen United States 13 57 0.4× 158 1.1× 63 0.4× 55 0.6× 47 0.5× 16 508
Paul Modlinger United States 8 55 0.4× 135 0.9× 69 0.5× 251 2.5× 91 1.0× 9 653
Munehiro Nakamura Japan 13 58 0.4× 153 1.0× 60 0.4× 93 0.9× 23 0.3× 18 640
Gianfranco Boccoli Italy 12 125 0.8× 93 0.6× 184 1.2× 50 0.5× 15 0.2× 21 650

Countries citing papers authored by Ray Fernando

Since Specialization
Citations

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

Fields of papers citing papers by Ray Fernando

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ray Fernando. 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 Ray Fernando. The network helps show where Ray Fernando may publish in the future.

Co-authorship network of co-authors of Ray Fernando

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

All Works

18 of 18 papers shown
1.
Shaw, Olivia, et al.. (2009). Investigations into the lack of consensus in the reporting of HLA antibody specificities in the UK. Journal of Clinical Pathology. 62(3). 270–274. 3 indexed citations
2.
Cox, S.T., et al.. (2008). Two novel MICA alleles, MICA*054 and MICA*056. Tissue Antigens. 73(1). 85–87. 3 indexed citations
3.
Fernando, Ray, et al.. (2007). Improving patient safety with a dedicated neuraxial connector – the CorrectInject © System. Anaesthesia. 62(3). 305–306. 3 indexed citations
4.
Fragopoulou, Elizabeth, Christos Iatrou, Smaragdi Antonopoulou, et al.. (2006). Platelet-activating factor (PAF) increase intracellular lipid accumulation by increasing both LDL and scavenger receptors in human mesangial cells. Journal of Laboratory and Clinical Medicine. 147(6). 281–289. 10 indexed citations
5.
Varghese, Zac, Ray Fernando, John F. Moorhead, Stephen H. Powis, & Xiong Z. Ruan. (2005). Effects of sirolimus on mesangial cell cholesterol homeostasis: a novel mechanism for its action against lipid-mediated injury in renal allografts. American Journal of Physiology-Renal Physiology. 289(1). F43–F48. 24 indexed citations
6.
Li, Hang, Xiong Z. Ruan, Stephen H. Powis, et al.. (2005). EPA and DHA reduce LPS-induced inflammation responses in HK-2 cells: Evidence for a PPAR-γ–dependent mechanism. Kidney International. 67(3). 867–874. 284 indexed citations
7.
Davenport, Andrew, Ray Fernando, & Zachariah Varghese. (2004). Intraperitoneal Nitric Oxide Production in Patients Treated by Continuous Ambulatory Peritoneal Dialysis. Blood Purification. 22(2). 216–223. 7 indexed citations
8.
Moorhead, J.F., et al.. (2004). Regulation of lipoprotein trafficking in the kidney: role of inflammatory mediators and transcription factors. Biochemical Society Transactions. 32(1). 88–91. 39 indexed citations
9.
Davenport, Andrew, Ray Fernando, Rachel L. Robson, & Z. Varghese. (2004). Nitric Oxide Production by Human Peritoneal Mesothelial Cells. The International Journal of Artificial Organs. 27(1). 15–23. 5 indexed citations
10.
Jf, Moorhead, et al.. (2003). Dysregulation of LDL receptor by an inflammatory cytokine: A new pathway for foam cell formation in vascular smooth muscle cells.. UCL Discovery (University College London). 7 indexed citations
11.
Varghese, Zac, Ray Fernando, Erasmia Psimenou, et al.. (1999). Calcineurin inhibitors enhance low-density lipoprotein oxidation in transplant patients. Kidney International. 56. S137–S140. 26 indexed citations
12.
Fernando, Ray, Zachariah Varghese, & John F. Moorhead. (1998). Differential ability of cells to promote oxidation of low density lipoproteins in vitro. Clinica Chimica Acta. 269(2). 159–173. 14 indexed citations
13.
Varghese, Z., Ray Fernando, Erasmia Psimenou, et al.. (1998). Oxidizability of low-density lipoproteins from neoral and tacrolimus-treated renal transplant patients. Transplantation Proceedings. 30(5). 2043–2046. 25 indexed citations
14.
Moorhead, John F., et al.. (1996). Do Glomerular Atherosclerosis and Lipid-Mediated Tubulo-lnterstitial Disease Cause Progressive Renal Failure in Man?. Blood Purification. 14(1). 58–66. 8 indexed citations
15.
Fernando, Ray, et al.. (1995). Estimation of time elapsed since death using entomological methods 1. 1 indexed citations
16.
Fernando, Ray, Z. Varghese, & J F Moorhead. (1993). Oxidation of low-density lipoproteins by rat mesangial cells and the interaction of oxidized low-density lipoproteins with rat mesangial cells in vitro. Nephrology Dialysis Transplantation. 8(6). 512–518. 22 indexed citations
17.
Wheeler, David C., Ray Fernando, Michael P.T. Gillett, et al.. (1991). Characterisation of the Binding of Low-Density Lipoproteins to Cultured Rat Mesangial Cells. Nephrology Dialysis Transplantation. 6(10). 701–708. 34 indexed citations
18.
Wheeler, David C., J.W. Persaud, Ray Fernando, et al.. (1990). Effects of Low-Density Lipoproteins on Mesangial Cell Growth and Viability In Vitro. Nephrology Dialysis Transplantation. 5(3). 185–191. 30 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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