Mary E. Edgerton

3.5k citations
46 papers · 2.4k · h-index 21

Impact in

Papers in

    • Gene expression and cancer classification 7
    • Bioinformatics and Genomic Networks 5
    • Biomedical Text Mining and Ontologies 4
    • Cancer Genomics and Diagnostics 5
    • Breast Cancer Treatment Studies 4

Mary E. Edgerton

44 papers receiving 2.4k citations

Peers

Mary E. Edgerton
Comparison fields: 5 of 122
  • Modeling and Simulation 223
  • Cancer Research 655
  • Oncology 684
  • Spectroscopy 323
  • Molecular Biology 1.2k
Replace Ingrid M. Meszoely with:
Ingrid M. Meszoely United States
Edward Gabrielson United States
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Citations per field
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Citations per year

Countries citing papers authored by Mary E. Edgerton

Since Specialization
Citations

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

Fields of papers citing papers by Mary E. Edgerton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003455
2 2018290
3
Significance of p63 amplification and overexpression in lung cancer development and prognosis.
2003255
4 2012162
5 2008157
6 2014114
7 2004112
8 2003112
9 2009106
10
A training-testing approach to the molecular classification of resected non-small cell lung cancer.
200394
11 200871
12 200356
13 201654
14 200944
15 201138
16 201136
17 201734
18 201132
19 201131
20 202428

About Mary E. Edgerton

Mary E. Edgerton is a scholar working on Molecular Biology, Cancer Research, Oncology, Pathology and Forensic Medicine and Surgery, having authored 46 papers that have together received 2.4k indexed citations. Recurring topics across this work include Gene expression and cancer classification (7 papers), Cancer Cells and Metastasis (6 papers), Cancer Genomics and Diagnostics (5 papers), Breast Lesions and Carcinomas (5 papers), Bioinformatics and Genomic Networks (5 papers), Breast Cancer Treatment Studies (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Mathematical Biology Tumor Growth (3 papers). The work is most often cited by research in Modeling and Simulation (223 citations), Cancer Research (655 citations), Oncology (684 citations), Spectroscopy (323 citations) and Molecular Biology (1.2k citations). Mary E. Edgerton has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Yu Shyr, Vittorio Cristini, Pierre P. Massion, David P. Carbone, John R. Roberts, Paul Macklin, Nicholas E. Navin, Tod D. Casasent, Sorena Nadaf and Kiyoshi Yanagisawa. Their work appears in journals such as Archives of Pathology & Laboratory Medicine, BMC Medical Informatics and Decision Making, BMC Medical Genomics, Cancer Research and Cancer Letters.

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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