Phyllis Moores

680 citations
39 papers · 492 · h-index 13

Impact in

  • Hematology top 5%
    • Blood groups and transfusion
  • Physiology top 10%
    • Erythrocyte Function and Pathophysiology

Papers in

    • Blood groups and transfusion 28
    • Erythrocyte Function and Pathophysiology 22

Phyllis Moores

37 papers receiving 415 citations

Peers

Phyllis Moores
Comparison fields: 5 of 73
  • Hematology 255
  • Physiology 198
  • Genetics 146
  • Genetics 53
  • Dermatology 27
Replace B. G. Pavone with:
B. G. Pavone United States
Gerald E. Bloom United States
Bainton Df United States
Isabelle Max‐Audit France
Shiro Ohnoki Japan
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V A McKusick United States
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Citations per field
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B. G. Pavone · 1×
Citations per year

Countries citing papers authored by Phyllis Moores

Since Specialization
Citations

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

Fields of papers citing papers by Phyllis Moores

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 195776
2 195766
3 198053
4 197524
5 195722
6 195720
7 197219
8 198618
9 197015
10 197514
11
On the relationship of the blood group antigens Mia and Vw to the MNSs system.
195814
12 198713
13 199012
14 199411
15 199110
16 199310
17 19729
18 19888
19 19948
20 19787

About Phyllis Moores

Phyllis Moores is a scholar working on Hematology, Physiology, Genetics, Epidemiology and Pediatrics, Perinatology and Child Health, having authored 39 papers that have together received 492 indexed citations. Recurring topics across this work include Blood groups and transfusion (28 papers), Erythrocyte Function and Pathophysiology (22 papers), Diabetes and associated disorders (8 papers), Blood disorders and treatments (4 papers), Herpesvirus Infections and Treatments (4 papers), Glycosylation and Glycoproteins Research (3 papers), Neonatal Health and Biochemistry (3 papers) and Parvovirus B19 Infection Studies (3 papers). The work is most often cited by research in Hematology (255 citations), Physiology (198 citations), Genetics (146 citations), Genetics (53 citations) and Dermatology (27 citations). Phyllis Moores has collaborated with scholars based in South Africa, United Kingdom and Croatia. Frequent co-authors include Ruth Sanger, R. R. Race, G. H. Findlay, Hannah B Lewis, William J. Weiner, P. B. Booth, Elizabeth W. Ikin, Jennifer James, Elizabeth Smart and D J Pudifin. Their work appears in journals such as Vox Sanguinis, Transfusion, Acta Haematologica, Human Heredity and British Journal of Haematology.

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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