Mary Moore

67 papers receiving 3.5k citations

Mary Moore's Hit Papers

Gain of function mutations in p53 1993 · 754 citations
7540+11+22Years since publication250500750

Peers

Mary Moore
Comparison fields: 5 of 174
  • Oncology 755
  • Biotechnology 220
  • Molecular Biology 1.5k
  • Developmental Biology 48
  • Genetics 571
Replace Yuji Ito with:
Yuji Ito Japan
Michael E. Baker United States
Robert P. Erickson United States
Francesco Piva Italy
Hiroaki Yamamoto Japan
Hiroshi Satō Japan
Rachel Allen United Kingdom
Michael J. Butler United States
Stephen M. Taylor Australia
Jyoti Malhotra United States
Mary Moore relative to Yuji Ito Japan Yuji Ito's profile →
Citations per field
00.5×4.4×
Yuji Ito · 1×
Citations per year

Countries citing papers authored by Mary Moore

Since Specialization
Citations

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

Fields of papers citing papers by Mary Moore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Gain of function mutations in p53
Hit paper breakdown →
1993754
2 1997446
3 1986269
4 2016244
5 1998167
6 2016151
7 2010140
8 2013104
9 200299
10 200290
11 199486
12 197683
13 198678
14 201266
15 200255
16 197850
17 200345
18 198744
19 200643
20 199042

About Mary Moore

Mary Moore is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, General Health Professions, Public Health, Environmental and Occupational Health and Infectious Diseases, having authored 72 papers that have together received 3.6k indexed citations. Recurring topics across this work include Health Sciences Research and Education (4 papers), Glycosylation and Glycoproteins Research (3 papers), Acupuncture Treatment Research Studies (3 papers), Electronic Health Records Systems (3 papers), Advanced Radiotherapy Techniques (3 papers), Cancer-related Molecular Pathways (3 papers), Viral gastroenteritis research and epidemiology (3 papers) and Climate variability and models (3 papers). The work is most often cited by research in Oncology (755 citations), Biotechnology (220 citations), Molecular Biology (1.5k citations), Developmental Biology (48 citations) and Genetics (571 citations). Mary Moore has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Arnold J. Levine, Gerard P. Zambetti, Cathy A. Finlay, Dirk P. Dittmer, Angelika K. Teresky, Thomas Shenk, Stephen H. Pilder, John S. Logan, Victor E. Shashoua and Zhiming Kuang. Their work appears in journals such as Annals of Internal Medicine, Molecular and Cellular Biology, Journal of Consulting and Clinical Psychology, Annals of Pharmacotherapy and Nature Genetics.

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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