Baruch Barzel

3.5k total citations · 1 hit paper
44 papers, 2.2k citations indexed

About

Baruch Barzel is a scholar working on Statistical and Nonlinear Physics, Molecular Biology and Modeling and Simulation. According to data from OpenAlex, Baruch Barzel has authored 44 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Statistical and Nonlinear Physics, 18 papers in Molecular Biology and 7 papers in Modeling and Simulation. Recurrent topics in Baruch Barzel's work include Complex Network Analysis Techniques (15 papers), Gene Regulatory Network Analysis (14 papers) and Opinion Dynamics and Social Influence (10 papers). Baruch Barzel is often cited by papers focused on Complex Network Analysis Techniques (15 papers), Gene Regulatory Network Analysis (14 papers) and Opinion Dynamics and Social Influence (10 papers). Baruch Barzel collaborates with scholars based in Israel, United States and China. Baruch Barzel's co-authors include Albert-Ĺaszló Barabási, Jianxi Gao, Ofer Biham, Yang‐Yu Liu, Gang Yan, Chittaranjan Hens, Simi Haber, George Tsekenis, Jean-Jacques Slotine and Reuven Cohen and has published in prestigious journals such as Nature, Physical Review Letters and Nature Communications.

In The Last Decade

Baruch Barzel

41 papers receiving 2.1k citations

Hit Papers

Universal resilience patterns in complex networks 2016 2026 2019 2022 2016 250 500 750
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.

  1. Universal resilience patterns in complex networks
    2016 781 citations Jianxi Gao, Baruch Barzel et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Baruch Barzel Israel 17 985 502 327 273 241 44 2.2k
Vincenzo Nicosia United Kingdom 25 1.7k 1.8× 433 0.9× 732 2.2× 220 0.8× 518 2.1× 67 3.4k
Raissa M. D’Souza United States 28 1.7k 1.7× 392 0.8× 826 2.5× 131 0.5× 137 0.6× 86 3.3k
Paulino Ribeiro Villas-Boas Brazil 20 1.1k 1.2× 334 0.7× 289 0.9× 95 0.3× 156 0.6× 49 2.8k
Mikhail Prokopenko Australia 29 954 1.0× 356 0.7× 311 1.0× 271 1.0× 742 3.1× 128 3.2k
Gonzalo Travieso Brazil 9 1.2k 1.3× 350 0.7× 314 1.0× 87 0.3× 169 0.7× 27 2.3k
André A. Moreira Brazil 25 1.8k 1.8× 420 0.8× 468 1.4× 71 0.3× 115 0.5× 68 2.8k
Thomas Richardson United Kingdom 22 841 0.9× 266 0.5× 262 0.8× 186 0.7× 375 1.6× 133 3.2k
Maya Paczuski United States 30 1.2k 1.2× 377 0.8× 218 0.7× 225 0.8× 212 0.9× 86 3.9k
Jobst Heitzig Germany 21 694 0.7× 176 0.4× 603 1.8× 561 2.1× 293 1.2× 69 2.3k
Keren Erez Israel 5 2.1k 2.1× 282 0.6× 676 2.1× 104 0.4× 58 0.2× 8 2.7k

Countries citing papers authored by Baruch Barzel

Since Specialization
Citations

This map shows the geographic impact of Baruch Barzel'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 Baruch Barzel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baruch Barzel more than expected).

Fields of papers citing papers by Baruch Barzel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Baruch Barzel. 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 Baruch Barzel. The network helps show where Baruch Barzel may publish in the future.

Co-authorship network of co-authors of Baruch Barzel

This figure shows the co-authorship network connecting the top 25 collaborators of Baruch Barzel. A scholar is included among the top collaborators of Baruch Barzel 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 Baruch Barzel. Baruch Barzel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Barzel, Baruch, et al.. (2026). Surface optimization governs the local design of physical networks. Nature. 649(8096). 315–322.
2.
Barzel, Baruch, et al.. (2025). Observing network dynamics through sentinel nodes. Nature Communications. 16(1). 10211–10211.
3.
Yu, Xinghu, Fangzhou Liu, Yang Shi, et al.. (2025). Privacy preserving optimization of communication networks. Nature Communications. 16(1). 8501–8501.
4.
Alfaro-Bittner, K., Ekaterina Vasilyeva, А. М. Райгородский, et al.. (2023). Why Are There Six Degrees of Separation in a Social Network?. Physical Review X. 13(2). 10 indexed citations
5.
Hens, Chittaranjan, et al.. (2023). Emergent stability in complex network dynamics. Nature Physics. 19(7). 1033–1042. 39 indexed citations
6.
Gao, Jianxi, et al.. (2022). Reviving a failed network through microscopic interventions. Nature Physics. 18(3). 338–349. 47 indexed citations
7.
Zhang, Xiyun, Zhongyuan Ruan, Muhua Zheng, et al.. (2022). Epidemic spreading under mutually independent intra- and inter-host pathogen evolution. Nature Communications. 13(1). 6218–6218. 27 indexed citations
8.
Sendiña–Nadal, I., Nagi Khalil, А. М. Райгородский, et al.. (2021). Growing scale-free simplices. Communications Physics. 4(1). 49 indexed citations
9.
Li, Zhaoqing, Zhenghong Deng, Zhen Han, et al.. (2021). Contagion in simplicial complexes. Chaos Solitons & Fractals. 152. 111307–111307. 45 indexed citations
10.
Zhang, Xiyun, Zhongyuan Ruan, Muhua Zheng, Baruch Barzel, & Stefano Boccaletti. (2020). Epidemic spreading under infection-reduced-recovery. Chaos Solitons & Fractals. 140. 110130–110130. 8 indexed citations
11.
Hens, Chittaranjan, et al.. (2020). Reply to: Asymptotic scaling describing signal propagation in complex networks. Nature Physics. 16(11). 1084–1085. 3 indexed citations
12.
Cohen, R., et al.. (2020). Alternating quarantine for sustainable mitigation of COVID-19. arXiv (Cornell University). 5 indexed citations
13.
Cohen, Reuven, et al.. (2019). Digitizable therapeutics for decentralized mitigation of global pandemics. Scientific Reports. 9(1). 14345–14345. 4 indexed citations
14.
Barzel, Baruch, et al.. (2017). Dynamic patterns of information flow in complex networks. Nature Communications. 8(1). 2181–2181. 104 indexed citations
15.
Barzel, Baruch, Yang‐Yu Liu, & Albert-Ĺaszló Barabási. (2015). Constructing minimal models for complex system dynamics. Nature Communications. 6(1). 7186–7186. 66 indexed citations
16.
Barzel, Baruch & Albert-Ĺaszló Barabási. (2013). Network link prediction by global silencing of indirect correlations. Nature Biotechnology. 31(8). 720–725. 194 indexed citations
17.
Barzel, Baruch & Albert-Ĺaszló Barabási. (2013). Universality in network dynamics. Nature Physics. 9(10). 673–681. 255 indexed citations
18.
Petit, Franck Le, Baruch Barzel, Ofer Biham, E. Roueff, & J. Le Bourlot. (2009). Incorporation of stochastic chemistry on dust grains \n in the Meudon PDR code using moment equations. Springer Link (Chiba Institute of Technology). 21 indexed citations
19.
Barzel, Baruch & Ofer Biham. (2009). Stochastic analysis of dimerization systems. Physical Review E. 80(3). 31117–31117. 5 indexed citations
20.
Barzel, Baruch & Ofer Biham. (2009). Quantifying the connectivity of a network: The network correlation function method. Physical Review E. 80(4). 46104–46104. 37 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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