Mathilde Badoual

2.0k total citations
40 papers, 1.4k citations indexed

About

Mathilde Badoual is a scholar working on Modeling and Simulation, Genetics and Molecular Biology. According to data from OpenAlex, Mathilde Badoual has authored 40 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Modeling and Simulation, 12 papers in Genetics and 6 papers in Molecular Biology. Recurrent topics in Mathilde Badoual's work include Mathematical Biology Tumor Growth (16 papers), Glioma Diagnosis and Treatment (12 papers) and Neural dynamics and brain function (6 papers). Mathilde Badoual is often cited by papers focused on Mathematical Biology Tumor Growth (16 papers), Glioma Diagnosis and Treatment (12 papers) and Neural dynamics and brain function (6 papers). Mathilde Badoual collaborates with scholars based in France, United States and Italy. Mathilde Badoual's co-authors include Christophe Deroulers, Thierry Bal, B. Grammaticos, Jacques Prost, Frank Jülicher, Yousheng Shu, Andrea R. Hasenstaub, David A. McCormick, Johan Pallud and Pascale Varlet and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Mathilde Badoual

39 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mathilde Badoual France 17 366 362 315 296 238 40 1.4k
Ingo Roeder Germany 30 502 1.4× 81 0.2× 96 0.3× 1.3k 4.3× 197 0.8× 109 2.8k
Maciej M. Mrugała United States 24 1.3k 3.4× 39 0.1× 115 0.4× 468 1.6× 459 1.9× 91 2.5k
James M. McFarland United States 19 79 0.2× 392 1.1× 251 0.8× 955 3.2× 29 0.1× 35 1.9k
Raghu Raghavan United States 24 365 1.0× 70 0.2× 332 1.1× 202 0.7× 26 0.1× 79 1.9k
Lijian Yang China 28 152 0.4× 1.1k 3.1× 256 0.8× 754 2.5× 39 0.2× 177 3.3k
E. Antonio Chiocca United States 22 364 1.0× 24 0.1× 59 0.2× 774 2.6× 408 1.7× 39 2.2k
Johan Pallud France 38 2.6k 7.0× 449 1.2× 670 2.1× 526 1.8× 226 0.9× 178 4.7k
Philippe Schucht Switzerland 28 1.2k 3.2× 121 0.3× 209 0.7× 150 0.5× 109 0.5× 109 2.5k
Kyrre E. Emblem Norway 29 930 2.5× 111 0.3× 620 2.0× 400 1.4× 58 0.2× 92 3.1k
Felix T. Kurz Germany 23 107 0.3× 57 0.2× 137 0.4× 316 1.1× 28 0.1× 104 1.4k

Countries citing papers authored by Mathilde Badoual

Since Specialization
Citations

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

Fields of papers citing papers by Mathilde Badoual

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mathilde Badoual

This figure shows the co-authorship network connecting the top 25 collaborators of Mathilde Badoual. A scholar is included among the top collaborators of Mathilde Badoual 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 Mathilde Badoual. Mathilde Badoual 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.
Plaszczynski, S., et al.. (2024). On the duration of face-to-face contacts. EPJ Data Science. 13(1). 1 indexed citations
2.
Plaszczynski, S., et al.. (2023). Predicting regrowth of low-grade gliomas after radiotherapy. PLoS Computational Biology. 19(3). e1011002–e1011002. 4 indexed citations
3.
Plaszczynski, S., et al.. (2021). The Effect of Radiotherapy on Diffuse Low-Grade Gliomas Evolution: Confronting Theory with Clinical Data. Journal of Personalized Medicine. 11(8). 818–818. 7 indexed citations
4.
Deroulers, Christophe, et al.. (2021). Effective epidemic model for COVID-19 using accumulated deaths. Chaos Solitons & Fractals. 144. 110667–110667. 7 indexed citations
5.
Seksek, Olivier, et al.. (2020). Modelling In Vitro Aggregation of Cancer Cells. Biophysical Journal. 118(3). 459a–459a. 1 indexed citations
6.
Deroulers, Christophe, et al.. (2020). Experimental and modeling study of the formation of cell aggregates with differential substrate adhesion. PLoS ONE. 15(2). e0222371–e0222371. 11 indexed citations
7.
Deroulers, Christophe, et al.. (2018). Modeling the dynamics of oligodendrocyte precursor cells and the genesis of gliomas. PLoS Computational Biology. 14(3). e1005977–e1005977. 12 indexed citations
8.
Dangouloff‐Ros, Volodia, Christophe Deroulers, Frantz Foissac, et al.. (2016). Arterial Spin Labeling to Predict Brain Tumor Grading in Children: Correlations between Histopathologic Vascular Density and Perfusion MR Imaging. Radiology. 281(2). 553–566. 79 indexed citations
9.
Deroulers, Christophe, et al.. (2013). Analyzing huge pathology images with open source software. Diagnostic Pathology. 8(1). 92–92. 73 indexed citations
10.
Pallud, Johan, Laurent Capelle, Luc Taillandier, et al.. (2013). The silent phase of diffuse low-grade gliomas. Is it when we missed the action?. Acta Neurochirurgica. 155(12). 2237–2242. 40 indexed citations
11.
Badoual, Mathilde, et al.. (2013). Exclusion processes: Short-range correlations induced by adhesion and contact interactions. Physical Review E. 87(1). 12702–12702. 7 indexed citations
12.
Regeard, Christophe, et al.. (2012). Modeling the role of water inBacillus subtiliscolonies. Physical Review E. 85(4). 41913–41913. 2 indexed citations
13.
Gerin, Chloé, Johan Pallud, B. Grammaticos, et al.. (2011). Improving the time‐machine: estimating date of birth of grade II gliomas. Cell Proliferation. 45(1). 76–90. 37 indexed citations
14.
Badoual, Mathilde, et al.. (2010). Modelling intercellular communication and its effects on tumour invasion. Physical Biology. 7(4). 46013–46013. 13 indexed citations
15.
Pallud, Johan, Pascale Varlet, Bertrand Devaux, et al.. (2010). Diffuse low-grade oligodendrogliomas extend beyond MRI-defined abnormalities. Neurology. 74(21). 1724–1731. 145 indexed citations
16.
Deroulers, Christophe, et al.. (2009). Modeling tumor cell migration: From microscopic to macroscopic models. Physical Review E. 79(3). 31917–31917. 92 indexed citations
17.
Badoual, Mathilde, et al.. (2008). A Model for Short- and Long-range Interactions of Migrating Tumour Cell. Acta Biotheoretica. 56(4). 297–314. 14 indexed citations
18.
Badoual, Mathilde, et al.. (2006). A cellular automaton model for the migration of glioma cells. Physical Biology. 3(2). 93–100. 52 indexed citations
19.
Destexhe, Alain, Mathilde Badoual, Zuzanna Piwkowska, Thierry Bal, & Michael Rudolph. (2004). A novel method for characterizing synaptic noise in cortical neurons. Neurocomputing. 58-60. 191–196. 8 indexed citations
20.
Cappello, Giovanni, Mathilde Badoual, Albrecht Ott, Jacques Prost, & Lorenzo Busoni. (2003). Kinesin motion in the absence of external forces characterized by interference total internal reflection microscopy. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 68(2). 21907–21907. 23 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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