Mark A. Eckert

4.2k citations
32 papers · 2.7k · 2 hit papers · h-index 19

Impact in

Papers in

    • Advanced biosensing and bioanalysis techniques 7
    • RNA modifications and cancer 4
    • Cancer Cells and Metastasis 6

Mark A. Eckert

31 papers receiving 2.7k citations

Mark A. Eckert's Hit Papers

Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts 2019 · 325 citations
3250+2+5Years since publication200400600

Peers

Mark A. Eckert
Comparison fields: 5 of 122
  • Cancer Research 798
  • Reproductive Medicine 266
  • Genetics 293
  • Molecular Biology 1.7k
  • Developmental Neuroscience 94
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Daniela Biziato Italy
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Silke Laßmann Germany
Anna Golebiewska Luxembourg
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Citations per year

Countries citing papers authored by Mark A. Eckert

Since Specialization
Citations

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

Fields of papers citing papers by Mark A. Eckert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark A. Eckert. 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 Mark A. Eckert. The network helps show where Mark A. Eckert may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
m6A mRNA methylation regulates AKT activity to promote the proliferation and tumorigenicity of endometrial cancer
Hit paper breakdown →
2018603
2 2011395
3
Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts
Hit paper breakdown →
2019325
4 2014162
5 2016154
6 2016130
7 2013124
8 2013101
9 2013100
10 201787
11 201973
12 201164
13 201353
14 201353
15 201445
16 201739
17 201534
18 201733
19 201726
20 202118

About Mark A. Eckert

Mark A. Eckert is a scholar working on Molecular Biology, Oncology, Cancer Research, Reproductive Medicine and Cell Biology, having authored 32 papers that have together received 2.7k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (7 papers), Ovarian cancer diagnosis and treatment (7 papers), Cancer Cells and Metastasis (6 papers), Mesenchymal stem cell research (4 papers), Cancer-related molecular mechanisms research (4 papers), Cancer, Hypoxia, and Metabolism (4 papers), RNA modifications and cancer (4 papers) and Cell Adhesion Molecules Research (3 papers). The work is most often cited by research in Cancer Research (798 citations), Reproductive Medicine (266 citations), Genetics (293 citations), Molecular Biology (1.7k citations) and Developmental Neuroscience (94 citations). Mark A. Eckert has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Ernst Lengyel, Weian Zhao, Jing Yang, Samantha M. Tienda, Jihoon Kim, Thinzar M. Lwin, Agnieszka Chryplewicz, Andrew Chang, Lucila Ohno‐Machado and Etienne Danis. Their work appears in journals such as Gynecologic Oncology, Oncotarget, Nature Communications, Cancer Cell and Scientific Reports.

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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