Mark A. Eckert

4.4k citations
35 papers · 3.3k · 3 hit papers · h-index 21

Impact in

Papers in

Mark A. Eckert

34 papers receiving 3.3k citations

Mark A. Eckert's Hit Papers

Deep Visual Proteomics defines single-cell identity and heterogeneity 2022 · 358 citations
3580+2+5Years since publication200400600

Peers

Mark A. Eckert
Comparison fields: 5 of 121
  • Cancer Research 753
  • Reproductive Medicine 264
  • Genetics 293
  • Molecular Biology 2.0k
  • Oncology 604
Replace Silke Laßmann with:
Silke Laßmann Germany
Chen Lu Huang China
Rodney Brian Luwor Australia
Daniela Biziato Italy
John Zevenhoven Netherlands
Devon A. Lawson United States
Brett William Stringer Australia
Sylvie Roberge United States
Christopher P. Vellano United States
Junke Zheng China
Mark A. Eckert relative to Silke Laßmann Germany Silke Laßmann's profile →
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Silke Laßmann · 1×
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 35 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 →
2018631
2 2011402
3
Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts
Hit paper breakdown →
2019397
4
Deep Visual Proteomics defines single-cell identity and heterogeneity
Hit paper breakdown →
2022358
5 2014176
6 2016161
7 2016159
8 2013130
9 2013115
10 2013107
11 2017100
12 201986
13 201166
14 201365
15 201356
16 201447
17 201943
18 201739
19 201536
20 201733

About Mark A. Eckert

Mark A. Eckert is a scholar working on Reproductive Medicine, Cancer Research, Oncology, Molecular Biology and Genetics, having authored 35 papers that have together received 3.3k indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (7 papers), Advanced biosensing and bioanalysis techniques (7 papers), Cancer Cells and Metastasis (6 papers), RNA modifications and cancer (4 papers), Cancer, Hypoxia, and Metabolism (4 papers), Mesenchymal stem cell research (4 papers), Cancer-related molecular mechanisms research (3 papers) and Cellular Mechanics and Interactions (3 papers). The work is most often cited by research in Cancer Research (753 citations), Reproductive Medicine (264 citations), Genetics (293 citations), Molecular Biology (2.0k citations) and Oncology (604 citations). Mark A. Eckert has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Ernst R. Lengyel, Weian Zhao, Jing Lan Yang, Samantha M. Tienda, Agnieszka Chryplewicz, Thinzar M. Lwin, Jihoon Kim, Lucila Ohno‐Machado, Etienne P. Danis and Kate Xie. Their work appears in journals such as Oncotarget, Gynecologic Oncology, Nature Communications, Interface Focus and Cancer Discovery.

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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