Matthias Großmann
- Molecular Biology
- Pulmonary and Respiratory Medicine top 10%
- Physiology top 10%
- Oncology
- Cancer Research top 10%
- Co-authors
- D. J. TindallHongxia HuangMargot P. ClearyKatai J. NkhataNancy K. MizunoWilhelm KirchBrian B. HoffmanOranee Tangphao
- Topics
- Data Management and Algorithms (9 papers)Context-Aware Activity Recognition Systems (5 papers)Ion channel regulation and function (5 papers)
- Journals
- BloodJournal of the American College of CardiologyJNCI Journal of the National Cancer Institute
- Partner nations
- GermanyUnited StatesSweden
In The Last Decade
Matthias Großmann
38 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 143
- Molecular Biology 539
- Pulmonary and Respiratory Medicine 376
- Physiology 230
- Oncology 203
- Cancer Research 181
Countries citing papers authored by Matthias Großmann
This map shows the geographic impact of Matthias Großmann'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 Matthias Großmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthias Großmann more than expected).
Fields of papers citing papers by Matthias Großmann
This network shows the impact of papers produced by Matthias Großmann. 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 Matthias Großmann. The network helps show where Matthias Großmann may publish in the future.
Co-authorship network of co-authors of Matthias Großmann
This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Großmann. A scholar is included among the top collaborators of Matthias Großmann 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 Matthias Großmann. Matthias Großmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 3 | |
| 3 | 8 | |
| 4 | Design Considerations of a Flexible Data Stream Processing Middleware. | 0 |
| 5 | 4 | |
| 6 | 8 | |
| 7 | Vertailte Datenstromverarbeitung von Sensordaten. | 1 |
| 8 | On Creating a Spatial Integration Schema for Global, Context-aware Applications. | 1 |
| 9 | 170 | |
| 10 | Keeping track of "flying elephants": Challenges in large-scale management of complex mobile objects | 4 |
| 11 | 23 | |
| 12 | 44 | |
| 13 | 3 | |
| 14 | 437 | |
| 15 | 15 | |
| 16 | 56 | |
| 17 | 46 | |
| 18 | 86 | |
| 19 | 90 | |
| 20 | 12 |
About Matthias Großmann
Matthias Großmann is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Physiology, having authored 39 papers that have together received 1.5k indexed citations. Recurring topics across this work include Data Management and Algorithms (9 papers), Context-Aware Activity Recognition Systems (5 papers) and Ion channel regulation and function (5 papers). The work is most often cited by research in Cancer Research (181 citations), Pulmonary and Respiratory Medicine (376 citations) and Endocrinology, Diabetes and Metabolism (154 citations). Matthias Großmann has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include D. J. Tindall, Hongxia Huang, Margot P. Cleary, Katai J. Nkhata, Nancy K. Mizuno, Wilhelm Kirch, Brian B. Hoffman, Oranee Tangphao, Terrence F. Blaschke and J. E. Perry. Their work appears in journals such as Blood, Journal of the American College of Cardiology and JNCI Journal of the National Cancer Institute.
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.