Michael T. Schaub

4.7k total citations · 3 hit papers
64 papers, 2.5k citations indexed

About

Michael T. Schaub is a scholar working on Statistical and Nonlinear Physics, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Michael T. Schaub has authored 64 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Statistical and Nonlinear Physics, 18 papers in Molecular Biology and 13 papers in Computational Theory and Mathematics. Recurrent topics in Michael T. Schaub's work include Complex Network Analysis Techniques (25 papers), Opinion Dynamics and Social Influence (15 papers) and Topological and Geometric Data Analysis (12 papers). Michael T. Schaub is often cited by papers focused on Complex Network Analysis Techniques (25 papers), Opinion Dynamics and Social Influence (15 papers) and Topological and Geometric Data Analysis (12 papers). Michael T. Schaub collaborates with scholars based in Germany, United Kingdom and United States. Michael T. Schaub's 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 and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.

In The Last Decade

Michael T. Schaub

58 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

SC3: consensus clustering of single-cell RNA-seq data

2017 920 citations Vladimir Yu Kiselev, Kristina Kirschner et al. Nature Methods profile →
Simplicial closure and higher-order link prediction

2018 321 citations Michael T. Schaub et al. profile →
What Are Higher-Order Networks?

2023 162 citations Christian Bick, Elizabeth Gross et al. SIAM Review profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael T. Schaub Germany	23	1.3k	605	373	256	222	64	2.5k
Chris H. Wiggins United States	29	2.9k 2.3×	383 0.6×	293 0.8×	143 0.6×	205 0.9×	59	4.9k
Ilya Nemenman United States	26	2.9k 2.3×	587 1.0×	510 1.4×	185 0.7×	322 1.5×	81	4.6k
Shmoolik Mangan Israel	6	3.5k 2.8×	582 1.0×	128 0.3×	132 0.5×	222 1.0×	6	4.2k
Adriano Barra Italy	26	747 0.6×	414 0.7×	427 1.1×	77 0.3×	93 0.4×	98	2.2k
Andrea Pagnani Italy	26	3.0k 2.3×	230 0.4×	188 0.5×	404 1.6×	305 1.4×	78	3.9k
Natali Gulbahce United States	15	2.8k 2.2×	325 0.5×	185 0.5×	359 1.4×	778 3.5×	26	4.2k
Ala Trusina Denmark	22	1.6k 1.3×	440 0.7×	51 0.1×	91 0.4×	105 0.5×	52	3.1k
Michal Sheffer United States	13	1.4k 1.1×	466 0.8×	105 0.3×	418 1.6×	130 0.6×	31	2.4k
Tianhai Tian Australia	26	1.8k 1.4×	269 0.4×	153 0.4×	108 0.4×	168 0.8×	140	3.0k
Daniel Marbach Switzerland	17	2.9k 2.3×	116 0.2×	310 0.8×	135 0.5×	218 1.0×	29	3.6k

Countries citing papers authored by Michael T. Schaub

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Nagai, James S., Tiago Maié, Michael T. Schaub, & Ivan G. Costa. (2025). scACCorDiON: a clustering approach for explainable patient level cell–cell communication graph analysis. Bioinformatics. 41(5). 1 indexed citations

Schaub, Michael T., et al.. (2025). Revealing drivers of green technology adoption through explainable Artificial Intelligence. Advances in Applied Energy. 20. 100242–100242. 1 indexed citations

Schaub, Michael T., et al.. (2025). A Bayesian Perspective on Uncertainty Quantification for Estimated Graph Signals. 1–5.

Arnaudon, Alexis, et al.. (2024). Algorithm 1044: PyGenStability, a Multiscale Community Detection Framework with Generalized Markov Stability. ACM Transactions on Mathematical Software. 50(2). 1–8. 5 indexed citations

Peel, Leto & Michael T. Schaub. (2024). Detectability of hierarchical communities in networks. Physical review. E. 110(3). 34306–34306.

Schaub, Michael T., et al.. (2023). Dirac signal processing of higher-order topological signals. New Journal of Physics. 25(9). 93013–93013. 23 indexed citations

Bick, Christian, Elizabeth Gross, Heather A. Harrington, & Michael T. Schaub. (2023). What Are Higher-Order Networks?. SIAM Review. 65(3). 686–731. 162 indexed citations breakdown →

Peisker, Fabian, Maurice Halder, James S. Nagai, et al.. (2022). Mapping the cardiac vascular niche in heart failure. Nature Communications. 13(1). 3027–3027. 53 indexed citations

Isufi, Elvin, et al.. (2022). Simplicial Convolutional Filters. IEEE Transactions on Signal Processing. 70. 4633–4648. 22 indexed citations

10.

Schaub, Michael T., et al.. (2021). Consensus dynamics on temporal hypergraphs. Oxford University Research Archive (ORA) (University of Oxford). 32 indexed citations

11.

Schaub, Michael T., et al.. (2021). State Aggregations in Markov Chains and Block Models of Networks. Physical Review Letters. 127(7). 78301–78301. 3 indexed citations

12.

Parise, Francesca, et al.. (2017). Centrality measures for graphons. arXiv (Cornell University). 2 indexed citations

13.

Kiselev, Vladimir Yu, Kristina Kirschner, Michael T. Schaub, et al.. (2017). SC3: consensus clustering of single-cell RNA-seq data. Nature Methods. 14(5). 483–486. 920 indexed citations breakdown →

14.

Billeh, Yazan N. & Michael T. Schaub. (2017). Feedforward architectures driven by inhibitory interactions. Journal of Computational Neuroscience. 44(1). 63–74. 3 indexed citations

15.

Schaub, Michael T., Jean‐Charles Delvenne, Sophia N. Yaliraki, & Mauricio Barahona. (2012). Markov Dynamics as a Zooming Lens for Multiscale Community Detection: Non Clique-Like Communities and the Field-of-View Limit. PLoS ONE. 7(2). e32210–e32210. 94 indexed citations

16.

Schaub, Michael T., Renaud Lambiotte, & Mauricio Barahona. (2011). Coding of Markov dynamics for multiscale community detection in complex networks. arXiv (Cornell University). 1 indexed citations

17.

Schaub, Michael T. & Simon R. Schultz. (2011). The Ising decoder: reading out the activity of large neural ensembles. Journal of Computational Neuroscience. 32(1). 101–118. 22 indexed citations

18.

Stadlbauer, Thomas, et al.. (2009). Apoptotic Cell Death During Accelerated Rejection in Sensitized Rat Recipients of Cardiac Allografts. Transplantation Proceedings. 41(6). 2621–2624. 1 indexed citations

19.

Göttmann, Uwe, Paul T. Brinkkoetter, Simone Hoeger, et al.. (2006). Effect of pre-treatment with catecholamines on cold preservation and ischemia/reperfusion-injury in rats. Kidney International. 70(2). 321–328. 31 indexed citations

20.

Bischoff, Serge, A. Bruinink, J. Krauss, et al.. (1992). CAN BRAIN REGION-SELECTIVE DOPAMINE (DA) RECEPTOR BLOCKERS PREFERENTIALLY ACT ON SCHIZOPHRENIA SUBTYPES?. Clinical Neuropharmacology. 15. 23A–24A. 2 indexed citations

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.

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