Ingo Bulla
Impact in
- Virology top 2%
- HIV Research and Treatment
- Infectious Diseases top 10%
- HIV/AIDS drug development and treatment
- HIV/AIDS Research and Interventions
Papers in
-
- Genomics and Phylogenetic Studies 6
- RNA and protein synthesis mechanisms 3
- Virology 8
- HIV Research and Treatment 7
- Co-authors
- Jan Bulla (7 shared papers)Thomas Leitner (7 shared papers)Anne-Kathrin Schultz (9 shared papers)Mario Stanke (7 shared papers)Burkhard Morgenstern (6 shared papers)Ethan Romero-Severson (6 shared papers)Bette Korber (4 shared papers)Ming Zhang (2 shared papers)
- Journals
- PLoS ONE (4 papers)Nucleic Acids Research (3 papers)BMC Bioinformatics (3 papers)Computational Statistics & Data Analysis (2 papers)International Journal of Research in Marketing (1 paper)
- Partner nations
- GermanyUnited StatesFrance
In The Last Decade
Ingo Bulla
32 papers receiving 909 citations
Peers
Comparison fields: 5 of 113
- Virology 271
- Infectious Diseases 209
- Finance 100
- Hepatology 42
- Parasitology 35
Countries citing papers authored by Ingo Bulla
This map shows the geographic impact of Ingo Bulla'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 Ingo Bulla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ingo Bulla more than expected).
Fields of papers citing papers by Ingo Bulla
This network shows the impact of papers produced by Ingo Bulla. 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 Ingo Bulla. The network helps show where Ingo Bulla may publish in the future.
Co-authors
The 25 scholars most cited alongside Ingo Bulla, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 119 | |
| 2 | 2006 | 112 | |
| 3 | 2010 | 93 | |
| 4 | 2016 | 66 | |
| 5 | 2012 | 64 | |
| 6 | 2014 | 64 | |
| 7 | 2008 | 58 | |
| 8 | 2022 | 45 | |
| 9 | 2011 | 40 | |
| 10 | 2016 | 39 | |
| 11 | 2011 | 37 | |
| 12 | 2019 | 34 | |
| 13 | 2021 | 29 | |
| 14 | 2019 | 22 | |
| 15 | 2019 | 15 | |
| 16 | 2012 | 11 | |
| 17 | 2017 | 10 | |
| 18 | 2010 | 8 | |
| 19 | 2014 | 8 | |
| 20 | 2018 | 8 |
About Ingo Bulla
Ingo Bulla is a scholar working on Molecular Biology, Virology, Infectious Diseases, Finance and Ecology, having authored 32 papers that have together received 927 indexed citations. Recurring topics across this work include HIV Research and Treatment (7 papers), Genomics and Phylogenetic Studies (6 papers), HIV/AIDS Research and Interventions (4 papers), Financial Risk and Volatility Modeling (3 papers), RNA and protein synthesis mechanisms (3 papers), Stochastic processes and financial applications (2 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers) and Evolution and Genetic Dynamics (2 papers). The work is most often cited by research in Virology (271 citations), Infectious Diseases (209 citations), Finance (100 citations), Hepatology (42 citations) and Parasitology (35 citations). Ingo Bulla has collaborated with scholars based in Germany, United States and France. Frequent co-authors include Jan Bulla, Thomas Leitner, Anne-Kathrin Schultz, Mario Stanke, Burkhard Morgenstern, Ethan Romero-Severson, Bette Korber, Ming Zhang, Oleg Nenadić and Christoph Grunau. Their work appears in journals such as PLoS ONE, Nucleic Acids Research, BMC Bioinformatics, Computational Statistics & Data Analysis and International Journal of Research in Marketing.
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.