Markus Bundschus
Impact in
- Health Informatics top 10%
- Artificial Intelligence top 5%
- Topic Modeling
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Natural Language Processing Techniques
Papers in
-
- Biomedical Text Mining and Ontologies 5
- Bioinformatics and Genomic Networks 2
- Genetics, Bioinformatics, and Biomedical Research 1
-
- Semantic Web and Ontologies 5
- Topic Modeling 3
- Advanced Text Analysis Techniques 1
- Co-authors
- Volker Tresp (5 shared papers)Hans‐Peter Kriegel (3 shared papers)M. Stetter (1 shared paper)Anna Bauer‐Mehren (2 shared papers)Ferrán Sanz (1 shared paper)Laura I. Furlong (2 shared papers)Miguel Ángel Mayer (1 shared paper)Michael Rautschka (1 shared paper)
- Journals
- Drug Discovery Today (2 papers)Proceedings of the IEEE (1 paper)BMC Bioinformatics (1 paper)Journal of Biomedical Semantics (1 paper)PLoS ONE (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Markus Bundschus
12 papers receiving 528 citations
Peers
Comparison fields: 5 of 112
- Health Informatics 15
- Artificial Intelligence 233
- Health Information Management 27
- Computational Theory and Mathematics 76
- Molecular Biology 315
Countries citing papers authored by Markus Bundschus
This map shows the geographic impact of Markus Bundschus'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 Markus Bundschus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Bundschus more than expected).
Fields of papers citing papers by Markus Bundschus
This network shows the impact of papers produced by Markus Bundschus. 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 Markus Bundschus. The network helps show where Markus Bundschus may publish in the future.
Co-authors
The 25 scholars most cited alongside Markus Bundschus, 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 | 2008 | 155 | |
| 2 | 2011 | 135 | |
| 3 | 2016 | 83 | |
| 4 | 2013 | 39 | |
| 5 | 2008 | 36 | |
| 6 | 2009 | 30 | |
| 7 | 2016 | 25 | |
| 8 | Materializing and Querying Learned Knowledge | 2009 | 23 |
| 9 | 2009 | 14 | |
| 10 | 2016 | 11 | |
| 11 | 2024 | 4 | |
| 12 | 2010 | 4 |
About Markus Bundschus
Markus Bundschus is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications and Information Systems, having authored 12 papers that have together received 559 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (5 papers), Biomedical Text Mining and Ontologies (5 papers), Computational Drug Discovery Methods (3 papers), Topic Modeling (3 papers), Bioinformatics and Genomic Networks (2 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Advanced Text Analysis Techniques (1 paper) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Health Informatics (15 citations), Artificial Intelligence (233 citations), Health Information Management (27 citations), Computational Theory and Mathematics (76 citations) and Molecular Biology (315 citations). Markus Bundschus has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Volker Tresp, Hans‐Peter Kriegel, M. Stetter, Anna Bauer‐Mehren, Ferrán Sanz, Laura I. Furlong, Miguel Ángel Mayer, Michael Rautschka, Shipeng Yu and Peter A. Fasching. Their work appears in journals such as Drug Discovery Today, Proceedings of the IEEE, BMC Bioinformatics, Journal of Biomedical Semantics and PLoS ONE.
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.