Mario Stanke
- Molecular Biology top 0.5%
- Plant Science top 0.2%
- Genetics top 0.5%
- Ecology top 1%
- Cell Biology top 0.5%
- Co-authors
- Burkhard MorgensternStephan WaackKatharina J. HoffMark BorodovskyAlexandre LomsadzeMark DiekhansDavid HausslerRobert Baertsch
- Topics
- Genomics and Phylogenetic Studies (41 papers)Machine Learning in Bioinformatics (24 papers)RNA and protein synthesis mechanisms (24 papers)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Mario Stanke
62 papers receiving 12.8k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Molecular Biology 7.4k
- Plant Science 5.2k
- Genetics 2.3k
- Ecology 1.6k
- Cell Biology 1.5k
Countries citing papers authored by Mario Stanke
This map shows the geographic impact of Mario Stanke'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 Stanke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Stanke more than expected).
Fields of papers citing papers by Mario Stanke
This network shows the impact of papers produced by Mario Stanke. 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 Stanke. The network helps show where Mario Stanke may publish in the future.
Co-authorship network of co-authors of Mario Stanke
This figure shows the co-authorship network connecting the top 25 collaborators of Mario Stanke. A scholar is included among the top collaborators of Mario Stanke 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 Stanke. Mario Stanke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 9 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 25 | |
| 6 | BRAKER2: automatic eukaryotic genome annotation with GeneMark-EP+ and AUGUSTUS supported by a protein databasebreakdown → | 803 |
| 7 | 7 | |
| 8 | 9 | |
| 9 | 60 | |
| 10 | 135 | |
| 11 | 38 | |
| 12 | 8 | |
| 13 | BRAKER1: Unsupervised RNA-Seq-Based Genome Annotation with GeneMark-ET and AUGUSTUSbreakdown → | 717 |
| 14 | 99 | |
| 15 | 8 | |
| 16 | 338 | |
| 17 | 366 | |
| 18 | 213 | |
| 19 | 19 | |
| 20 | Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sourcesbreakdown → | 837 |
About Mario Stanke
Mario Stanke is a scholar working on Virology, Molecular Biology and Plant Science, having authored 63 papers that have together received 12.9k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (41 papers), Machine Learning in Bioinformatics (24 papers) and RNA and protein synthesis mechanisms (24 papers). The work is most often cited by research in Plant Science (5.2k citations), Horticulture (119 citations) and Molecular Biology (7.4k citations). Mario Stanke has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Burkhard Morgenstern, Stephan Waack, Katharina J. Hoff, Mark Borodovsky, Alexandre Lomsadze, Mark Diekhans, David Haussler, Robert Baertsch, Irfan Gunduz and O. Keller. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.
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.