M. Graessmann
Impact in
- Genetics top 5%
- Virus-based gene therapy research
- Molecular Biology top 5%
- Epigenetics and DNA Methylation
- RNA Interference and Gene Delivery
- CRISPR and Genetic Engineering
- Genomics and Chromatin Dynamics
- RNA Research and Splicing
Papers in
-
- RNA Interference and Gene Delivery 9
- CRISPR and Genetic Engineering 7
- RNA and protein synthesis mechanisms 7
- RNA Research and Splicing 6
- Oncology 24
- Polyomavirus and related diseases 20
- Co-authors
- A. Graessmann (56 shared papers)Eva Guhl (11 shared papers)B. Wittig (1 shared paper)Christian Mueller (3 shared papers)Christian Mueller (4 shared papers)William C. Topp (2 shared papers)Yin‐Jeh Tzeng (4 shared papers)Andreas Klein (6 shared papers)
In The Last Decade
M. Graessmann
59 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 95
- Genetics 682
- Molecular Biology 1.4k
- Oncology 519
- Cell Biology 166
- Biotechnology 80
Countries citing papers authored by M. Graessmann
This map shows the geographic impact of M. Graessmann'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 M. Graessmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Graessmann more than expected).
Fields of papers citing papers by M. Graessmann
This network shows the impact of papers produced by M. Graessmann. 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 M. Graessmann. The network helps show where M. Graessmann may publish in the future.
Co-authors
The 25 scholars most cited alongside M. Graessmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1987 | 222 | |
| 2 | 1976 | 206 | |
| 3 | 1980 | 151 | |
| 4 | 1983 | 141 | |
| 5 | 1978 | 93 | |
| 6 | 1980 | 67 | |
| 7 | 1995 | 62 | |
| 8 | 1983 | 59 | |
| 9 | 1974 | 47 | |
| 10 | Breast cancer formation in transgenic animals induced by the whey acidic protein SV40 T antigen (WAP-SV-T) hybrid gene. | 1993 | 47 |
| 11 | 2006 | 45 | |
| 12 | 1989 | 41 | |
| 13 | 1985 | 41 | |
| 14 | 1979 | 41 | |
| 15 | 2003 | 37 | |
| 16 | 1994 | 36 | |
| 17 | 2009 | 36 | |
| 18 | 1977 | 32 | |
| 19 | 1981 | 32 | |
| 20 | 1976 | 29 |
About M. Graessmann
M. Graessmann is a scholar working on Molecular Biology, Oncology, Genetics, Ecology and Cardiology and Cardiovascular Medicine, having authored 60 papers that have together received 2.0k indexed citations. Recurring topics across this work include Virus-based gene therapy research (22 papers), Polyomavirus and related diseases (20 papers), Bacteriophages and microbial interactions (11 papers), RNA Interference and Gene Delivery (9 papers), CRISPR and Genetic Engineering (7 papers), Viral Infections and Immunology Research (7 papers), RNA and protein synthesis mechanisms (7 papers) and RNA Research and Splicing (6 papers). The work is most often cited by research in Genetics (682 citations), Molecular Biology (1.4k citations), Oncology (519 citations), Cell Biology (166 citations) and Biotechnology (80 citations). M. Graessmann has collaborated with scholars based in Germany, Taiwan and Brazil. Frequent co-authors include A. Graessmann, Eva Guhl, B. Wittig, Christian Mueller, Christian Mueller, William C. Topp, Yin‐Jeh Tzeng, Andreas Klein, Christoph Mueller and Robert Tjian. Their work appears in journals such as FEBS Letters, Nucleic Acids Research, Proceedings of the National Academy of Sciences, Journal of Virology and Oncogene.
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.