Michael T. Schaub
- Molecular Biology top 10%
- Statistical and Nonlinear Physics top 1%
- Artificial Intelligence top 5%
- Cancer Research top 10%
- Computational Theory and Mathematics top 2%
- Co-authors
- Mauricio BarahonaTallulah AndrewsVladimir Yu KiselevMartin HembergKristina KirschnerKedar Nath NatarajanAnthony R. GreenAndrew Yiu
- Topics
- Complex Network Analysis Techniques (25 papers)Opinion Dynamics and Social Influence (15 papers)Topological and Geometric Data Analysis (12 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersNature Communications
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Michael T. Schaub
58 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Molecular Biology 1.3k
- Statistical and Nonlinear Physics 605
- Artificial Intelligence 373
- Cancer Research 256
- Computational Theory and Mathematics 222
Countries citing papers authored by Michael T. Schaub
This map shows the geographic impact of Michael T. Schaub'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 Michael T. Schaub with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael T. Schaub more than expected).
Fields of papers citing papers by Michael T. Schaub
This network shows the impact of papers produced by Michael T. Schaub. 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 Michael T. Schaub. The network helps show where Michael T. Schaub may publish in the future.
Co-authorship network of co-authors of Michael T. Schaub
This figure shows the co-authorship network connecting the top 25 collaborators of Michael T. Schaub. A scholar is included among the top collaborators of Michael T. Schaub 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 Michael T. Schaub. Michael T. Schaub is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 23 | |
| 7 | What Are Higher-Order Networks?breakdown → | 162 |
| 8 | 53 | |
| 9 | 22 | |
| 10 | Consensus dynamics on temporal hypergraphs | 32 |
| 11 | 3 | |
| 12 | Centrality measures for graphons | 2 |
| 13 | SC3: consensus clustering of single-cell RNA-seq databreakdown → | 920 |
| 14 | 3 | |
| 15 | 94 | |
| 16 | Coding of Markov dynamics for multiscale community detection in complex networks | 1 |
| 17 | 22 | |
| 18 | 1 | |
| 19 | 31 | |
| 20 | 2 |
About Michael T. Schaub
Michael T. Schaub is a scholar working on Statistical and Nonlinear Physics, Transplantation and Computational Mathematics, having authored 64 papers that have together received 2.5k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (25 papers), Opinion Dynamics and Social Influence (15 papers) and Topological and Geometric Data Analysis (12 papers). The work is most often cited by research in Statistical and Nonlinear Physics (605 citations), Biophysics (174 citations) and Computational Mathematics (16 citations). Michael T. Schaub has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Mauricio Barahona, Tallulah Andrews, Vladimir Yu Kiselev, Martin Hemberg, Kristina Kirschner, Kedar Nath Natarajan, Anthony R. Green, Andrew Yiu, Wolf Reik and Tamir Chandra. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.
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.