Javier Buceta

1.9k total citations
65 papers, 1.3k citations indexed

About

Javier Buceta is a scholar working on Molecular Biology, Computer Networks and Communications and Condensed Matter Physics. According to data from OpenAlex, Javier Buceta has authored 65 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 16 papers in Computer Networks and Communications and 16 papers in Condensed Matter Physics. Recurrent topics in Javier Buceta's work include Nonlinear Dynamics and Pattern Formation (16 papers), Theoretical and Computational Physics (13 papers) and Cellular Mechanics and Interactions (12 papers). Javier Buceta is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (16 papers), Theoretical and Computational Physics (13 papers) and Cellular Mechanics and Interactions (12 papers). Javier Buceta collaborates with scholars based in Spain, United States and United Kingdom. Javier Buceta's co-authors include Katja Lindenberg, Juan M. R. Parrondo, F. Javier de la Rubia, Marc Weber, Ramón Reigada, Marta Ibañes, Christian Van den Broeck, Francesc Sagués, Carlos Escudero and Oriol Canela‐Xandri 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

Javier Buceta

64 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Javier Buceta Spain	23	525	360	278	212	197	65	1.3k
Radek Erban United Kingdom	26	1.3k 2.4×	414 1.1×	335 1.2×	202 1.0×	305 1.5×	71	2.2k
Cyrill B. Muratov United States	26	458 0.9×	485 1.3×	527 1.9×	138 0.7×	181 0.9×	93	2.0k
Lutz Brusch Germany	22	669 1.3×	185 0.5×	242 0.9×	323 1.5×	165 0.8×	57	1.6k
Anna L. Lin United States	15	292 0.6×	258 0.7×	390 1.4×	206 1.0×	71 0.4×	37	1.0k
M. A. Tsyganov Russia	19	279 0.5×	255 0.7×	392 1.4×	167 0.8×	101 0.5×	58	1.1k
Cristián Huepe United States	21	371 0.7×	472 1.3×	756 2.7×	92 0.4×	242 1.2×	44	2.2k
Jay Newby United States	23	1.0k 2.0×	428 1.2×	81 0.3×	169 0.8×	262 1.3×	43	1.7k
Anna Zafeiris Hungary	5	329 0.6×	512 1.4×	639 2.3×	103 0.5×	445 2.3×	8	2.1k
Anotida Madzvamuse United Kingdom	24	372 0.7×	110 0.3×	590 2.1×	332 1.6×	141 0.7×	84	1.8k
Carsten Beta Germany	27	473 0.9×	422 1.2×	452 1.6×	551 2.6×	691 3.5×	92	2.0k

Countries citing papers authored by Javier Buceta

Since Specialization

Citations

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

Fields of papers citing papers by Javier Buceta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Javier Buceta

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

All Works

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20 of 20 papers shown

Buceta, Javier, et al.. (2025). Physical communication pathways in bacteria: an extra layer to quorum sensing. Biophysical Reviews. 17(2). 667–685. 2 indexed citations

Bocchini, Paolo, et al.. (2024). Stochastic analysis of Ebola infection in small zoonotic niches. Royal Society Open Science. 11(11). 240298–240298.

Buceta, Javier, et al.. (2023). Comprehensive profiling of neutralizing polyclonal sera targeting coxsackievirus B3. Nature Communications. 14(1). 6417–6417. 3 indexed citations

Conus, Daniel, et al.. (2023). Random field calibration with data on irregular grid for regional analyses: A case study on the bare carrying capacity of bats in Africa. Ecology and Evolution. 13(9). e10489–e10489. 1 indexed citations

Smith, Anna, et al.. (2022). Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors. PLoS ONE. 17(9). e0271886–e0271886. 3 indexed citations

Gómez‐Gálvez, Pedro, Ana M. Palacios, Valentina Annese, et al.. (2022). A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia. Cell Systems. 13(8). 631–643.e8. 9 indexed citations

Gómez‐Gálvez, Pedro, et al.. (2021). The complex three-dimensional organization of epithelial tissues. Development. 148(1). 22 indexed citations

Gómez‐Gálvez, Pedro, et al.. (2021). Mechanics and self-organization in tissue development. Seminars in Cell and Developmental Biology. 120. 147–159. 17 indexed citations

Mageeney, Catherine M., et al.. (2020). Mycobacterium Phage Butters-Encoded Proteins Contribute to Host Defense against Viral Attack. mSystems. 5(5). 13 indexed citations

10.

Canela‐Xandri, Oriol, et al.. (2020). TiFoSi : an efficient tool for mechanobiology simulations of epithelia. Bioinformatics. 36(16). 4525–4526. 7 indexed citations

11.

Pouille, Philippe‐Alexandre, et al.. (2019). Mechanical coordination is sufficient to promote tissue replacement during metamorphosis in Drosophila. The EMBO Journal. 39(3). e103594–e103594. 8 indexed citations

12.

Butzin, Nicholas C., et al.. (2019). A Cell Segmentation/Tracking Tool Based on Machine Learning. Methods in molecular biology. 2040. 399–422. 10 indexed citations

13.

Gómez‐Gálvez, Pedro, Florencia Cavodeassi, Sol Sotillos, et al.. (2018). Scutoids are a geometrical solution to three-dimensional packing of epithelia. Nature Communications. 9(1). 2960–2960. 99 indexed citations

14.

Buceta, Javier. (2013). Multidisciplinary approaches towards compartmentalization in development: Dorsoventral boundary formation of the Drosophila wing disc as a case study. 9(1). 57–66. 1 indexed citations

15.

Weber, Marc & Javier Buceta. (2013). Dynamics of the quorum sensing switch: stochastic and non-stationary effects. BMC Systems Biology. 7(1). 6–6. 46 indexed citations

16.

Saade, Murielle, Gwenvaël Le Dréau, M. Angeles Rabadán, et al.. (2013). Sonic Hedgehog Signaling Switches the Mode of Division in the Developing Nervous System. Cell Reports. 4(3). 492–503. 70 indexed citations

17.

Ullner, Ekkehard, Javier Buceta, Antoni Díez‐Noguera, & Jordi García‐Ojalvo. (2009). Noise-Induced Coherence in Multicellular Circadian Clocks. Biophysical Journal. 96(9). 3573–3581. 47 indexed citations

18.

Canela‐Xandri, Oriol, Francesc Sagués, Ramón Reigada, & Javier Buceta. (2008). A Spatial Toggle Switch Drives Boundary Formation in Development. Biophysical Journal. 95(11). 5111–5120. 8 indexed citations

19.

Buceta, Javier, Marta Ibañes, J. M. Sancho, & Katja Lindenberg. (2003). Noise-driven mechanism for pattern formation. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 67(2). 21113–21113. 59 indexed citations

20.

Buceta, Javier, Katja Lindenberg, & Juan M. R. Parrondo. (2002). Pattern formation induced by nonequilibrium global alternation of dynamics. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 66(3). 36216–36216. 22 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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