Mario Amendola
- Molecular Biology top 1%
- Genetics top 2%
- Cancer Research top 2%
- Immunology top 5%
- Oncology top 5%
- Co-authors
- Bas van SteenselEva K. BrinkmanTao ChenLuigi NaldiniBernhard GentnerJean‐Luc GaffardBrian D. BrownLudo Pagie
- Topics
- Economic theories and models (12 papers)CRISPR and Genetic Engineering (11 papers)Virus-based gene therapy research (10 papers)
- Partner nations
- ItalyFranceUnited States
In The Last Decade
Mario Amendola
59 papers receiving 5.8k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Molecular Biology 4.5k
- Genetics 1.1k
- Cancer Research 716
- Immunology 592
- Oncology 533
Countries citing papers authored by Mario Amendola
This map shows the geographic impact of Mario Amendola'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 Mario Amendola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Amendola more than expected).
Fields of papers citing papers by Mario Amendola
This network shows the impact of papers produced by Mario Amendola. 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 Mario Amendola. The network helps show where Mario Amendola may publish in the future.
Co-authorship network of co-authors of Mario Amendola
This figure shows the co-authorship network connecting the top 25 collaborators of Mario Amendola. A scholar is included among the top collaborators of Mario Amendola 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 Mario Amendola. Mario Amendola is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 11 | |
| 4 | 27 | |
| 5 | 93 | |
| 6 | 17 | |
| 7 | 2 | |
| 8 | 145 | |
| 9 | 98 | |
| 10 | 85 | |
| 11 | 332 | |
| 12 | Inequality debt and taxation the perverse relation between the productive and the non productive assets of the economy | 0 |
| 13 | Single-Cell Dynamics of Genome-Nuclear Lamina Interactionsbreakdown → | 500 |
| 14 | 47 | |
| 15 | 68 | |
| 16 | Forebrain ependymal cells are Notch-dependent and generate neuroblasts and astrocytes after strokebreakdown → | 352 |
| 17 | 449 | |
| 18 | Out of Equilibrium | 61 |
| 19 | Flexibilité, information et décision | 14 |
| 20 | Towards a Dynamic Analysis of the "Traverse" | 0 |
About Mario Amendola
Mario Amendola is a scholar working on General Economics, Econometrics and Finance, Genetics and Economics and Econometrics, having authored 63 papers that have together received 5.9k indexed citations. Recurring topics across this work include Economic theories and models (12 papers), CRISPR and Genetic Engineering (11 papers) and Virus-based gene therapy research (10 papers). The work is most often cited by research in Developmental Neuroscience (300 citations), Molecular Biology (4.5k citations) and Aging (99 citations). Mario Amendola has collaborated with scholars based in Italy, France and United States. Frequent co-authors include Bas van Steensel, Eva K. Brinkman, Tao Chen, Luigi Naldini, Bernhard Gentner, Jean‐Luc Gaffard, Brian D. Brown, Ludo Pagie, Jop Kind and Sandra S. de Vries. Their work appears in journals such as Cell, Nucleic Acids Research and Nature Communications.
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.