Keiko Mayne

1.1k total citations
17 papers, 849 citations indexed

About

Keiko Mayne is a scholar working on Molecular Biology, Cell Biology and Hematology. According to data from OpenAlex, Keiko Mayne has authored 17 papers receiving a total of 849 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Cell Biology and 5 papers in Hematology. Recurrent topics in Keiko Mayne's work include Proteoglycans and glycosaminoglycans research (8 papers), Glycosylation and Glycoproteins Research (5 papers) and Blood groups and transfusion (4 papers). Keiko Mayne is often cited by papers focused on Proteoglycans and glycosaminoglycans research (8 papers), Glycosylation and Glycoproteins Research (5 papers) and Blood groups and transfusion (4 papers). Keiko Mayne collaborates with scholars based in Australia, United Kingdom and United States. Keiko Mayne's co-authors include Carmela Ricciardelli, Norman Davidson, Wayne D. Tilley, Robert J. LaPolla, David J. Horsfall, Andrew J. Sakko, Richard G. LeBaron, Supaporn Suwiwat, Villis R. Marshall and Henry A. Lester and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of General Physiology.

In The Last Decade

Keiko Mayne

17 papers receiving 832 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Keiko Mayne Australia	12	590	397	118	96	89	17	849
Nijole Gasiunas United Kingdom	9	495 0.8×	354 0.9×	80 0.7×	120 1.3×	129 1.4×	12	703
Naoko Kogata United Kingdom	12	598 1.0×	207 0.5×	89 0.8×	149 1.6×	184 2.1×	20	895
Annika N. Alexopoulou United Kingdom	8	340 0.6×	221 0.6×	119 1.0×	95 1.0×	46 0.5×	9	632
M. C. Kibbey United States	10	445 0.8×	195 0.5×	155 1.3×	183 1.9×	73 0.8×	15	872
D. McCormick United Kingdom	15	371 0.6×	219 0.6×	234 2.0×	198 2.1×	40 0.4×	34	768
F. Gumkowski United States	9	349 0.6×	295 0.7×	93 0.8×	128 1.3×	25 0.3×	9	728
Adi D. Dubash United States	17	759 1.3×	466 1.2×	76 0.6×	134 1.4×	55 0.6×	22	1.2k
Jürg Zumbrunn Switzerland	8	615 1.0×	391 1.0×	50 0.4×	110 1.1×	96 1.1×	12	901
Jun-Lin Guan United States	10	695 1.2×	354 0.9×	206 1.7×	156 1.6×	100 1.1×	10	1.2k
Tuvia Peretz Israel	8	976 1.7×	885 2.2×	109 0.9×	125 1.3×	129 1.4×	11	1.2k

Countries citing papers authored by Keiko Mayne

Since Specialization

Citations

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

Fields of papers citing papers by Keiko Mayne

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keiko Mayne

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

All Works

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17 of 17 papers shown

Mayne, Keiko, et al.. (2008). 'Partial D’women with anti-D alloimmunization in pregnancy. Clinical & Laboratory Haematology. 13(3). 239–244. 10 indexed citations

Mayne, Keiko, et al.. (2008). The significance of anti-S sensitization in pregnancy. Clinical & Laboratory Haematology. 12(1). 105–107. 14 indexed citations

Mayne, Keiko, et al.. (2008). The significance of anti-Kell sensitization in pregnancy. Clinical & Laboratory Haematology. 12(4). 379–385. 8 indexed citations

Ricciardelli, Carmela, Darryl L. Russell, Miranda P. Ween, et al.. (2007). Formation of Hyaluronan- and Versican-rich Pericellular Matrix by Prostate Cancer Cells Promotes Cell Motility. Journal of Biological Chemistry. 282(14). 10814–10825. 122 indexed citations

Sakko, Andrew J., Carmela Ricciardelli, Keiko Mayne, et al.. (2006). Changes in steroid receptors and proteoglycan expression in the guinea pig prostate stroma during puberty and hormone manipulation. The Prostate. 67(3). 288–300. 8 indexed citations

Sakko, Andrew J., Carmela Ricciardelli, Keiko Mayne, et al.. (2003). Modulation of prostate cancer cell attachment to matrix by versican.. PubMed. 63(16). 4786–91. 72 indexed citations

Ricciardelli, Carmela, John H M Brooks, Supaporn Suwiwat, et al.. (2002). Regulation of stromal versican expression by breast cancer cells and importance to relapse-free survival in patients with node-negative primary breast cancer.. PubMed. 8(4). 1054–60. 137 indexed citations

Sakko, Andrew J., et al.. (2001). Versican accumulation in human prostatic fibroblast cultures is enhanced by prostate cancer cell-derived transforming growth factor beta1.. PubMed. 61(3). 926–30. 89 indexed citations

Ricciardelli, Carmela, Keiko Mayne, Pamela J. Sykes, et al.. (1997). Elevated stromal chondroitin sulfate glycosaminoglycan predicts progression in early-stage prostate cancer.. PubMed. 3(6). 983–92. 77 indexed citations

10.

Horsfall, David J., Keiko Mayne, John M. Skinner, et al.. (1994). Glycosaminoglycans of guinea pig prostate fibromuscular stroma: Influence of estrogen and androgen on levels and location of chondroitin sulfate. The Prostate. 25(6). 320–332. 13 indexed citations

11.

Suzuki, Koji, Keiko Mayne, Ian Doyle, & Rosemary L. Ryall. (1994). Urinary glycosaminoglycans are selectively included into calcium oxalate crystals precipitated from whole human urine.. PubMed. 8(3). 523–30. 12 indexed citations

12.

Pulford, Karen, Kingsley Micklem, Francesco Pezzella, et al.. (1994). A novel internal antigen which distinguishes germinal centre cells from other B-cell types.. PubMed. 82(1). 154–63. 5 indexed citations

13.

Mayne, Keiko, Karen Pulford, Margaret T. Jones, et al.. (1993). Antibody By 114 is selective for the 90 kD PI‐linked component of the CD66 antigen: a new reagent for the study of paroxysmal nocturnal haemoglobinuria. British Journal of Haematology. 83(1). 30–38. 22 indexed citations

14.

Mayne, Keiko & E. J. Maher. (1989). Near-haploid cell line in megakaryoblastic transformation of Philadelphia-positive chronic myeloid leukemia. Cancer Genetics and Cytogenetics. 39(1). 133–136. 2 indexed citations

15.

Yu, Liang, et al.. (1987). Equilibrium properties of mouse-Torpedo acetylcholine receptor hybrids expressed in Xenopus oocytes.. The Journal of General Physiology. 90(4). 553–573. 47 indexed citations

16.

White, M M, Keiko Mayne, Henry A. Lester, & Nicholas O. Davidson. (1985). Mouse-Torpedo hybrid acetylcholine receptors: functional homology does not equal sequence homology.. Proceedings of the National Academy of Sciences. 82(14). 4852–4856. 82 indexed citations

17.

LaPolla, Robert J., Keiko Mayne, & Norman Davidson. (1984). Isolation and characterization of a cDNA clone for the complete protein coding region of the delta subunit of the mouse acetylcholine receptor.. Proceedings of the National Academy of Sciences. 81(24). 7970–7974. 129 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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