Danielle Martinet
- Genetics top 10%
- Virus-based gene therapy research 4
- Genomic variations and chromosomal abnormalities 4
- Chronic Lymphocytic Leukemia Research 3
- Genetics top 5%
- Virus-based gene therapy research 4
- Genomic variations and chromosomal abnormalities 4
- Chronic Lymphocytic Leukemia Research 3
- Molecular Biology top 10%
- RNA Interference and Gene Delivery 4
- CRISPR and Genetic Engineering 4
- Viral Infectious Diseases and Gene Expression in Insects 3
- Genomics and Chromatin Dynamics 3
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- Chronic Myeloid Leukemia Treatments 3
- Co-authors
- J. BeckmannNicolas MermodRoland MeierMarjorie FlahautAnnick Mühlethaler‐MottetAurélie CoulonPierre‐Alain GirodKatya Nardou
- Cited by
- GeneticsMolecular Biology
- Journals
- The American Journal of Human Genetics (2 papers)Oncogene (2 papers)Nature Methods (1 paper)
- Partner nations
- SwitzerlandFranceUnited States
In The Last Decade
Danielle Martinet
26 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 85
- Genetics 144
- Genetics 342
- Molecular Biology 767
- Cancer Research 145
- Cell Biology 107
Countries citing papers authored by Danielle Martinet
This map shows the geographic impact of Danielle Martinet'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 Danielle Martinet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Martinet more than expected).
Fields of papers citing papers by Danielle Martinet
This network shows the impact of papers produced by Danielle Martinet. 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 Danielle Martinet. The network helps show where Danielle Martinet may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Danielle Martinet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 49 | |
| 2 | 2015 | 36 | |
| 3 | 2015 | 50 | |
| 4 | 2013 | 16 | |
| 5 | 2013 | 58 | |
| 6 | 2012 | 69 | |
| 7 | 2011 | 13 | |
| 8 | 2011 | 45 | |
| 9 | 2010 | 68 | |
| 10 | 2009 | 0 | |
| 11 | 2009 | 84 | |
| 12 | 2009 | 153 | |
| 13 | 2008 | 27 | |
| 14 | 2008 | 20 | |
| 15 | 2007 | 114 | |
| 16 | 2006 | 19 | |
| 17 | 2005 | 108 | |
| 18 | 1999 | 7 | |
| 19 | 1999 | 25 | |
| 20 | 1997 | 26 |
About Danielle Martinet
Danielle Martinet is a scholar working on Genetics, Genetics and Developmental Biology, having authored 27 papers that have together received 1.1k indexed citations. Recurring topics across this work include Virus-based gene therapy research (4 papers), RNA Interference and Gene Delivery (4 papers), Genomic variations and chromosomal abnormalities (4 papers), CRISPR and Genetic Engineering (4 papers), Chronic Lymphocytic Leukemia Research (3 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers), Chronic Myeloid Leukemia Treatments (3 papers) and Genomics and Chromatin Dynamics (3 papers). The work is most often cited by research in Genetics (144 citations), Genetics (342 citations) and Molecular Biology (767 citations). Danielle Martinet has collaborated with scholars based in Switzerland, France and United States. Frequent co-authors include J. Beckmann, Nicolas Mermod, Roland Meier, Marjorie Flahaut, Annick Mühlethaler‐Mottet, Aurélie Coulon, Pierre‐Alain Girod, Katya Nardou, Felix Niggli and David Calabrese. Their work appears in journals such as The American Journal of Human Genetics, Oncogene, Nature Methods, Clinical Cancer Research and Biotechnology and Bioengineering.
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.