María C. Marín

5.3k citations
71 papers · 4.3k indexed · 4 hit papers · h-index 32
Topics
Cancer-related Molecular Pathways (24 papers)Cancer Research and Treatments (11 papers)Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers)

In The Last Decade

María C. Marín

70 papers receiving 4.2k citations

Hit Papers

p73 is a human p53-related protein that can induce apoptosis19972026200620161997200020002003250500750

Peers

María C. Marín
Comparison fields: 5 of 115
  • Molecular Biology 2.8k
  • Oncology 2.6k
  • Biotechnology 939
  • Cancer Research 552
  • Genetics 338
Replace Kanaga Sabapathy with:
Kanaga Sabapathy Singapore
L A Donehower United States
Laurie B. Owen‐Schaub United States
Daniele Bergamaschi United Kingdom
Qimin Zhan United States
Julia I-Ju Leu United States
Shan Zhong China
Laszlo Jakoi United States
Daniel B. Levy United States
B Hoffman United States
María C. Marín relative to Kanaga Sabapathy Singapore Kanaga Sabapathy's profile →
Citations per field
00.5×2.6×
Kanaga Sabapathy · 1×
Citations per year

Countries citing papers authored by María C. Marín

Since Specialization
Citations

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

Fields of papers citing papers by María C. Marín

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by María C. Marín. 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 María C. Marín. The network helps show where María C. Marín may publish in the future.

Co-authorship network of co-authors of María C. Marín

This figure shows the co-authorship network connecting the top 25 collaborators of María C. Marín. A scholar is included among the top collaborators of María C. Marín based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with María C. Marín. María C. Marín is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 6
4 5
5 33
6 18
7 24
8 52
9 30
10 42
11 37
12 26
13 20
14 5
15
Chemosensitivity linked to p73 functionbreakdown →
345
16 29
17 88
18
Role for the p53 homologue p73 in E2F-1-induced apoptosisbreakdown →
592
19
Expression of bcl-2 gene confers multidrug resistance to chemotherapy- induced cell death
14
20 2

About María C. Marín

María C. Marín is a scholar working on Biotechnology, Oncology and Developmental Neuroscience, having authored 71 papers that have together received 4.3k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (24 papers), Cancer Research and Treatments (11 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers). The work is most often cited by research in Biotechnology (939 citations), Oncology (2.6k citations) and Molecular Biology (2.8k citations). María C. Marín has collaborated with scholars based in Spain, United States and Argentina. Frequent co-authors include William G. Kaelin, Christine A. Jost, Meredith S. Irwin, Timothy J. McDonnell, Karen H. Vousden, Lynn S. Cheng, Keiichi Kondo, William C. Hahn, Elsa R. Flores and Jeremy C. Smith. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

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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