Tanja Kellner
Impact in
- Cancer Research top 0.5%
- Cancer-related molecular mechanisms research
- Molecular Biology top 0.5%
- Genomics and Chromatin Dynamics
- RNA modifications and cancer
- RNA Research and Splicing
- Epigenetics and DNA Methylation
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
Papers in
-
- CRISPR and Genetic Engineering 4
- Genomics and Chromatin Dynamics 3
- RNA and protein synthesis mechanisms 3
- Pluripotent Stem Cells Research 1
- RNA Research and Splicing 1
-
- Chromosomal and Genetic Variations 2
- Co-authors
- Joachim Wittbrodt (5 shared papers)Thomas Thumberger (3 shared papers)Beate Wittbrodt (3 shared papers)Erika Tsingos (1 shared paper)Kerim Anlaş (1 shared paper)Katharina Lust (1 shared paper)Lázaro Centanin (1 shared paper)William A. Harris (1 shared paper)
- Journals
- Development (2 papers)Disease Models & Mechanisms (1 paper)Nucleic Acids Research (1 paper)Nature (1 paper)eLife (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Tanja Kellner
7 papers receiving 15.6k citations
Tanja Kellner's Hit Papers
Peers
Comparison fields: 5 of 164
- Cancer Research 3.4k
- Molecular Biology 11.7k
- Genetics 3.2k
- Aging 87
- Immunology 936
Countries citing papers authored by Tanja Kellner
This map shows the geographic impact of Tanja Kellner'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 Tanja Kellner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tanja Kellner more than expected).
Fields of papers citing papers by Tanja Kellner
This network shows the impact of papers produced by Tanja Kellner. 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 Tanja Kellner. The network helps show where Tanja Kellner may publish in the future.
Co-authors
The 18 scholars most cited alongside Tanja Kellner, 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 | An integrated encyclopedia of DNA elements in the human genome Hit paper breakdown → | 2012 | 13299 |
| 2 | An integrated encyclopedia of DNA elements in the human genome Hit paper breakdown → | 2012 | 2353 |
| 3 | 2018 | 77 | |
| 4 | 2014 | 48 | |
| 5 | 2022 | 11 | |
| 6 | 2012 | 10 | |
| 7 | 2023 | 4 |
About Tanja Kellner
Tanja Kellner is a scholar working on Molecular Biology, Plant Science, Cell Biology, Genetics and Insect Science, having authored 7 papers that have together received 15.8k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Genomics and Chromatin Dynamics (3 papers), RNA and protein synthesis mechanisms (3 papers), Chromosomal and Genetic Variations (2 papers), Zebrafish Biomedical Research Applications (1 paper), Animal Genetics and Reproduction (1 paper), Pluripotent Stem Cells Research (1 paper) and RNA Research and Splicing (1 paper). The work is most often cited by research in Cancer Research (3.4k citations), Molecular Biology (11.7k citations), Genetics (3.2k citations), Aging (87 citations) and Immunology (936 citations). Tanja Kellner has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Joachim Wittbrodt, Thomas Thumberger, Beate Wittbrodt, Erika Tsingos, Kerim Anlaş, Katharina Lust, Lázaro Centanin, William A. Harris, Burkhard Hoeckendorf and Benjamin David Simons. Their work appears in journals such as Development, Disease Models & Mechanisms, Nucleic Acids Research, Nature and eLife.
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.