Mark D’Amico

3.9k citations
15 papers · 3.3k indexed · 1 hit paper · h-index 14

Mark D’Amico

15 papers receiving 3.3k citations

Hit Papers

The cyclin D1 gene is a target of the β-catenin/LEF-1 pat...1.9k199920262008201750010001.5k

Peers

Mark D’Amico
Comparison fields: 5 of 107
  • Molecular Biology 2.7k
  • Oncology 1.0k
  • Cancer Research 461
  • Cell Biology 352
  • Pathology and Forensic Medicine 234
Replace Osamu Tetsu with:
Osamu Tetsu United States
Andreas Marti Switzerland
Shunyou Wang United States
Anna C. Schinzel United States
Radha P. Narsimhan United States
Frauke Bataille Germany
Leonard Girnita Sweden
Pedro J. Real Spain
Yong Wen United States
Valeriana Di Castro Italy
Mark D’Amico relative to Osamu Tetsu United States Osamu Tetsu's profile →
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Citations per year

Countries citing papers authored by Mark D’Amico

Since Specialization
Citations

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

Fields of papers citing papers by Mark D’Amico

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark D’Amico. 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 D’Amico. The network helps show where Mark D’Amico may publish in the future.

Co-authorship network

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

All Works

15 of 15 papers shown
#Work
1 200817
2 200718
3 20054
4 200433
5 2003131
6 2003107
7 2003189
8
The role of Ink4a/Arf in ErbB2 mammary gland tumorigenesis.
200325
9
Flavopiridol and trastuzumab synergistically inhibit proliferation of breast cancer cells: association with selective cooperative inhibition of cyclin D1-dependent kinase and Akt signaling pathways.
200252
10 2000305
11 200048
12 1999160
13 1999253
14
The cyclin D1 gene is a target of the β-catenin/LEF-1 pathwaybreakdown →
19991913
15 199948

About Mark D’Amico

Mark D’Amico is a scholar working on Oncology, Cancer Research, Molecular Biology, Reproductive Medicine and Biotechnology, having authored 15 papers that have together received 3.3k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (9 papers), Cancer-related gene regulation (4 papers), Cell death mechanisms and regulation (3 papers), RNA modifications and cancer (2 papers), Epigenetics and DNA Methylation (2 papers), NF-κB Signaling Pathways (2 papers), Mechanisms of cancer metastasis (1 paper) and Virus-based gene therapy research (1 paper). The work is most often cited by research in Molecular Biology (2.7k citations), Oncology (1.0k citations), Cancer Research (461 citations), Cell Biology (352 citations) and Pathology and Forensic Medicine (234 citations). Mark D’Amico has collaborated with scholars based in United States, Israel and South Korea. Frequent co-authors include Richard G. Pestell, Chris Albanese, Avri Ben‐Ze'ev, Inbal Simcha, Michael Shtutman, Jacob Zhurinsky, Maofu Fu, Richard J. Lee, Genichi Watanabe and Kongming Wu. Their work appears in journals such as Journal of Biological Chemistry, Molecular Biology of the Cell, Nature Genetics, Investigational New Drugs and Cell Cycle.

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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