PUBLICATIONS

A LA UNE

2024

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Gaume, B., Achitouv, I., & Chavalarias, D. (2024). A Unified Graph Clustering Framework for Complex Systems Modeling. https://hal.science/hal-04505654

Nichols, R., Charbonneau, M., Chellappoo, A., Davis, T., Haidle, M., Kimbrough, E. O., Moll, H., Moore, R., Scott-Phillips, T., Purzycki, B. G., & Segovia-Martin, J. (2024). Cultural evolution: A review of theoretical challenges. Evolutionary Human Sciences, 6, e12. https://doi.org/10.1017/ehs.2024.2

Briot, J.-P., de Azevedo Irving, M., & Alvarez, I. (2024). Gestion participative de parcs et espaces protégés : le projet SimParc. https://hal.science/hal-04408269

Chavalarias, D., Bouchaud, P., & Panahi, M. (2024). Can a Single Line of Code Change Society? The Systemic Risks of Optimizing Engagement in Recommender Systems on Global Information Flow, Opinion Dynamics and Social Structures. Journal of Artificial Societies and Social Simulation, 27(1), 9. https://www.jasss.org/27/1/9.html

Gaume, B., Architouv, I., & Chavalarias, D. (2024). A binary classifier of node Pairs by node Blocks to find graph custering, with or without overlaps.

Çetin, P. B., Raziye Buse. (2024, January 25). Auditing Amazon Recommender Systems: Insights Into Risk Assessment Under The Digital Services Act | TechPolicy.Press. Tech Policy Press. https://techpolicy.press/auditing-amazon-recommender-systems-insights-into-risk-assessment-under-the-digital-services-act

Peralta, A. F., Ramaciotti, P., Kertész, J., & Iñiguez, G. (2024). Multidimensional political polarization in online social networks (No. arXiv:2305.02941). arXiv. https://doi.org/10.48550/arXiv.2305.02941

Cassells, D., Tabourier, L., & Ramaciotti, P. (2024, April). Modeling both pairwise interactions and group effects in polarization on interaction networks. International Conference on Complex Networks. https://hal.science/hal-04363001

Ramaciotti, P., Cassells, D., Vagena, Z., Cointet, J.-P., & Bailey, M. (2024). American politics in 3D: measuring multidimensional issue alignment in social media using social graphs and text data. Applied Network Science, 9(1), 2. https://doi.org/10.1007/s41109-023-00608-w

Boucahud P., Liénard, J.F.,Beyond the Guidelines: Assessing Meta’s Political Ad Moderation in the EU, IMC ’24: Proceedings of the 2024 ACM on Internet Measurement Conference Pages 480 – 487

https://doi.org/10.1145/3646547.3689020

Bouchaud, P., Ramaciotti, P. Auditing the audits: evaluating methodologies for social media recommender system audits. Appl Netw Sci 9, 59 (2024). https://doi.org/10.1007/s41109-024-00668-6

2023

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Rojas-Velazquez, D., Tonda, A., Rodriguez-Guerra, I., Kraneveld, A. D., & Lopez-Rincon, A. (2023). Multi-objective Evolutionary Discretization of Gene Expression Profiles: Application to COVID-19 Severity Prediction. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation (pp. 703–717). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-30229-9_45

Squillero, G., & Tonda, A. (2023). Veni, Vidi, Evolvi commentary on W. B. Langdon’s “Jaws 30.” Genetic Programming and Evolvable Machines, 24(2), 24. https://doi.org/10.1007/s10710-023-09472-0

Ndim, M., Raimbault, J., Bucher, B., Olteanu-Raimond, A.-M., & Perret, J. (2023, September). A collaborative dashboard to study periurban densification. European Colloquium on Theoretical and Quantitative Geography 2023. https://hal.science/hal-04257790

Raimbault, J., & Pumain, D. (2023, July 24). Innovation dynamics in multi-scalar systems of cities. ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference. https://doi.org/10.1162/isal_a_00702

Towards Unlocking the Linguistic Code of Post-Traumatic Stress Disorder: A Comprehensive Analysis and Diagnostic Approach. (2023, December 19). https://doi.org/10.21203/rs.3.rs-3747882/v1

Pierrot-Valroff. (2023). A Complex Systems Approach of Existential Risks. EHESS.

Chavalarias, D., Bouchaud, P., Chomel, V., & Panahi, M. (2023). Les nouveaux fronts du dénialisme et du climato-scepticisme (pre-print No. hal-03986798; ISC-PIF working papers). Institut des Systèmes Complexes de Paris Île-de-France. https://hal.science/hal-03986798

Chavalarias, D., Bouchaud, P., Chomel, V., & Panahi, M. (2023). The new fronts of denialism and climate skepticism (No. hal-04103183). HAL Science. https://hal.science/hal-04103183

Lobbé, Q., Chavalarias, D., & Delanoë, A. (2023). Defining Level and Scale as Socio-technical Operators for Mining Digital Traces. In Defining Level and Scale as Socio-technical Operators for Mining Digital Traces (pp. 407–426). De Gruyter Oldenbourg. https://doi.org/10.1515/9783111317779-015

Faverjon, T., & Ramaciotti, P. (2023, November). Discovering ideological structures in representation learning spaces in recommender systems on social media data. 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. https://doi.org/10.1145/3625007.3627336

Bouchaud, P., Chavalarias, D., & Panahi, M. (2023). Crowdsourced audit of Twitter’s recommender systems. Scientific Reports, 13(1), 16815. https://doi.org/10.1038/s41598-023-43980-4

2022

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David Chavalarias, mathématicien: “Les réseaux sociaux ont rendu les dictatures plus stables qu’auparavant.” (2022, March 19). L’Echo. https://www.lecho.be/opinions/general/david-chavalarias-mathematicien-les-reseaux-sociaux-ont-rendu-les-dictatures-plus-stables-qu-auparavant/10374637.html

Widyastuti, K., Reuillon, R., Chapron, P., Abdussalam, W., Nasir, D., Harrison, M. E., Morrogh-Bernard, H., Imron, M. A., & Berger, U. (2022). Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans—An agent-based modeling approach. Frontiers in Ecology and Evolution, 10, 983337. https://doi.org/10.3389/fevo.2022.983337

Sermondadaz, S. (2022, April 9). Présidentielle française: les algorithmes votent pour l’extrême droite. Heidi News. https://www.heidi.news/sciences-climat/presidentielle-francaise-les-algorithmes-votent-pour-l-extreme-droite

Schwarz, F. (2022, March 19). Les trolls de Poutine - Désinformation en temps de guerre - Regarder le documentaire complet [Documentaires et reportages]. In ARTE. https://www.arte.tv/fr/videos/107710-044-A/les-trolls-de-poutine/

Pain, J. (2022, April 16). “Vrai ou Fake”, les intox des candidats. In Franceinfo. https://www.francetvinfo.fr/replay-magazine/franceinfo/vrai-ou-fake-l-emission/vrai-ou-fake-l-emission-du-samedi-16-avril-2022_5085649.html

deutschlandfunk.de. (n.d.). #Presidentielle2022: Die Rolle der Sozialen Medien im französischen Wahlkampf. Deutschlandfunk. Retrieved April 7, 2022, from https://www.deutschlandfunk.de/presidentielle2022-die-rolle-der-sozialen-medien-im-franzoesischen-wahlkampf-dlf-2627cf1e-100.html

Chomel, V., Panahi, M., & Chavalarias, D. (2022, 2022). Modeling social network evolution over time using Graph Neural Networks to detect polarisation. 6 Th European Conference on Social Networks.

Chomel, V., Panahi, M., & Chavalarias, D. (2022). Manipulation during the French presidential campaign: coordinated inauthentic behaviors and astroturfing analysis on text and images. 1077. https://doi.org/10.1007/978-3-031-21127-0_11

Chomel, V., Cuvelle-Magar, N., & Chavalarias, D. (2022). Scalable and reliable anomaly detection on Dynamic Graph based on link prediction to identify disinformation. https://hal.archives-ouvertes.fr/hal-03866467

Chomel, V., Cuvelle-Magar, N., Panahi, M., & Chavalarias, D. (2022, November 17). Polarization identification on multiple timescale using representation learning on temporal graphs in Eulerian description. NeurIPS 2022 Temporal Graph Learning Workshop. https://openreview.net/forum?id=P_MSQXnNhS

Chomel, V. (2022). Beyond Fake News: a structural and dynamic approach towards analyzing online misinformation and manipulation of public opinion. EHESS.

Chavalarias, D., Huneman, P., & Racovski, T. (2022). Contribution of phylomemies to the understanding of the dynamics of science. In G. Ramsey & A. de Block (Eds.), The dynamics of science: computational frontiers in history and philosophy of science. University of Pittsburgh Press.

Chavalarias, D., Chomel, V., & Panahi, M. (2022, April 21). L’extrême droite arrivera-t-elle à supprimer le vote Macron? – Libération. Libération. https://www.liberation.fr/idees-et-debats/tribunes/lextreme-droite-arrivera-t-elle-a-supprimer-le-vote-macron-20220421_PONBRKCQZZGIFOE5BXSP6B5DP4/

Chavalarias, D. (2022). Mathématiques présidentielles La révolution du « jugement majoritaire ». Grief, 9(1), 59–82.

Chavalarias, D. (2022). Shifting Collectives. In 12th Berlin Biennale for Contemporary Art. https://12.berlinbiennale.de/

Chavalarias, D. (2022, April 9). Comment les algorithmes influencent nos comportements électoraux (M. Saliou, Interviewer) [Slate.fr]. http://www.slate.fr/story/226047/election-presidentielle-manipulations-algorithmes-influencent-comportements-electoraux-vote

Chavalarias, D. (2022, April 8). « Toxic data », livre antidote en période électorale (F. Savatier, Interviewer) [Pour la Science]. https://www.pourlascience.fr/sd/sciences-sociales/https:https://www.pourlascience.fr/sd/sciences-sociales/toxic-data-livre-antidote-en-periode-electorale-23688.php

Chavalarias, D. (2022, April 6). Présidentielle 2022 : quelles manipulations sur les réseaux sociaux ? (A. Abdelbost, Interviewer) [France24]. https://twitter.com/France24_fr/status/1511777006089695235

Achour, M. (2022, March 18). Clique. In myCANAL. https://www.canalplus.com/actualites/clique/h/12270209_50001

2021

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Lobbé, Q., Delanoë, A., & Chavalarias, D. (2021). Exploring, browsing and interacting with multi-scale structures of knowledge. https://hal.archives-ouvertes.fr/hal-03181233

Lobbé, Q., Delanoë, A., & Chavalarias, D. (2021). Exploring, browsing and interacting with multi-level and multi-scale dynamics of knowledge. Information Visualization, 14738716211044828. https://doi.org/10.1177/14738716211044829

Chavalarias, D., Lobbé, Q., & Delanoë, A. (2021). Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies. Scientometrics. https://doi.org/10.1007/s11192-021-04186-5

Chavalarias, D., Lobbe, Q., & Delanoë, A. (2021). Draw me Science - multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies. https://hal.archives-ouvertes.fr/hal-03180347

Chavalarias, D. (2021). Étude de la diffusion du film Hold-up. In A. Basdevant & R. Harfoush (Eds.), Récits et contre-récits (Conseil National du Numérique, pp. 58–62).

2020

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Verbavatz, V., & Barthelemy, M. (2020). The growth equation of cities. Nature, 587(7834), 397–401. https://doi.org/10.1038/s41586-020-2900-x

Raimbault, J. (2020). Published: 20 November 2019 Second-order control of complex systems with correlated synthetic data. Nature. https://doi.org/https://doi.org/10.1186/s40294-019-0065-y

Raimbault, J. (2020, January 31). Hierarchy and co-evolution processes in urban systems. https://arxiv.org/pdf/2001.11989.pdf

Lin, K., Chavalarias, D., Panahi, M., Yeh, T., Takimoto, K., & Mizoguchi, M. (2020). Mobile-based traceability system for sustainable food supply networks. Nature Food, 1–7. https://doi.org/10.1038/s43016-020-00163-y

Kosowska-Stamirowska, Z. (2020). Network effects govern the evolution of maritime trade. PNAS, 117 (23) 12719-12728. https://doi.org/https://doi.org/10.1073/pnas.1906670117

Gaget, A., Montanier, J.-M., & Doursat, R. (2020). Branched Structure Formation in a Decentralized Flock of Wheeled Robots. volume 12421. https://doi.org/https://doi.org/10.1007/978-3-030-60376-2_4

Chavalarias, D. (2020). What’s wrong with Science ? https://hal.archives-ouvertes.fr/hal-01354988

Chavalarias, D. (2020). From inert matter to the global society - Life as multi-level networks of processes. Philosophical Transactions of the Royal Society B: Biological Sciences. https://doi.org/http://dx.doi.org/10.1098/rstb.2019.0329

ARCHIVES

2019

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Wilmet, A., & Lamarche-Perrin, R. (2019). Multidimensional Outlier Detection in Interaction Data: Application to Political Communication on Twitter. CompleNet 2019: Complex Networks X, pp 147-155. https://doi.org/https://doi.org/10.1007/978-3-030-14459-3_12

Raimbault, J., Cottineau, C., Le Texier, M., Le Nechet, F., & Reuillon, R. (2019). Space Matters: Extending Sensitivity Analysis to Initial Spatial Conditions in Geosimulation Models. Journal of Artificial Societies and Social Simulation, 22(4). https://doi.org/10.18564/jasss.4136

Raimbault, J. (2019). Generating urban morphologies at large scales. https://arxiv.org/abs/1903.06807

Raimbault, J. (2019). Multi-dimensional Urban Network Percolation. https://arxiv.org/abs/1903.07141

Raimbault, J. (2019). Second-order control of complex systems with correlated synthetic data. Complex Adaptive Systems Modeling. https://doi.org/https://doi.org/10.1186/s40294-019-0065-y

Raimbault, J. (2019, December). Worldwide estimation of parameters for a simple reaction-diffusion model of urban growth. International Land-use Symposium 2019, Paris, France. https://halshs.archives-ouvertes.fr/halshs-02406539/

Raimbault, J. (2019, Février). Towards multi-scalar models for the co-evolution of transportation networks and territories. Theo Quant 2019, Besançon, France. https://halshs.archives-ouvertes.fr/halshs-02013006/

Chavalarias, D., Panahi, M., & Gaumont, N. (2019). Politoscope. In K. Börner & E. Record (Eds.), 15th Iteration (2019): Macroscopes for Tracking the Flow of Resources. http://scimaps.org

Chavalarias, D., Gaumont, N., & Panahi, M. (2019). Hostilité et prosélytisme des communautés politiques. Reseaux, n° 214-215(2), 67–107. http://www.cairn.info/revue-reseaux-2019-2-page-67.htm

Chavalarias, D. (2019). Les Formes de l’Intelligence Collective. In A. Fleischer & A. Prochiantz (Eds.), Le Rêve des formes. Arts, sciences & Cie (Seuil, pp. 145–152).

Botterman, H.-L., & Lamarche-Perrin, R. (2019, March 6). Combining Path-Constrained Random Walks to Recover Link Weights in Heterogeneous Information Networks. 10th Conference on Complex Networks CompleNet 2019. https://doi.org/https://doi.org/10.1007/978-3-030-14459-3_8

Baudot, P., Tapia, M., Bennequin, D., & Goaillard, J.-M. (2019). Topological Information Data Analysis. Entropy, 21, 869. https://doi.org/10.3390/e21090869

Baudot, P. (2019). Elements of qualitative cognition: An information topology perspective. Physics of Life Reviews. https://doi.org/10.1016/j.plrev.2019.10.003

Baudot, P. (2019). The Poincaré-Shannon Machine: Statistical Physics and Machine Learning Aspects of Information Cohomology. Entropy, 21(9), 881. https://doi.org/10.3390/e21090881

2018

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La présidentielle 2017 au prisme de Twitter. (2018, September 19). CNRS Le journal. https://lejournal.cnrs.fr/articles/la-presidentielle-2017-au-prisme-de-twitter

Wilmet, A., Viard, T., Latapy, M., & Lamarche-Perrin, R. (2018). Degree-based Outliers Detection within IP Traffic Modelled as a Link Stream. http://www.complexnetworks.fr/wp-content/uploads/2018/06/accepted_version_article.pdf

Sénécat, A. (2018, September 19). Intox, polarisation, risques de manipulation : les leçons de la présidentielle vue de Twitter. Le Monde.fr. https://www.lemonde.fr/le-blog-du-decodex/article/2018/09/19/intox-polarisation-risques-de-manipulation-les-lecons-de-la-presidentielle-vue-de-twitter_5357508_5095029.html

La Dépeche. (2018, September 19). Fake news : ce sont les pro-Fillon qui en auraient partagé le plus pendant la Présidentielle. ladepeche.fr. https://www.ladepeche.fr/article/2018/09/20/2872449-fake-news-sont-pro-fillon-auraient-partage-plus-pendant-presidentielle.html

L’Express. (2018, September 21). Fillonistes, mélenchonistes ou macronistes, qui a fait quoi sur Twitter pendant la présidentielle 2017. LExpress.fr. https://www.lexpress.fr/actualite/politique/fillonistes-melenchonistes-ou-macronistes-qui-a-fait-quoi-sur-twitter-pendant-la-presidentielle-2017_2036143.html

Gaumont, N., Panahi, M., & Chavalarias, D. (2018). Reconstruction of the socio-semantic dynamics of political activist Twitter networks—Method and application to the 2017 French presidential election. PLOS ONE, 13(9), e0201879. https://doi.org/10.1371/journal.pone.0201879

Chavalarias, D., Panahi, M., & Gaumont, N. (2018). Climate Tweetoscope. In K. Börner & E. Record (Eds.), 14th Iteration (2018): Macroscopes for Ensuring our Well-being. http://scimaps.org

Chavalarias, D. (2018, November 14). A l’ère numérique, nos démocraties doivent évoluer pour ne pas mourir. AOC media - Analyse Opinion Critique. https://aoc.media/analyse/2018/11/14/a-lere-numerique-nos-democraties-doivent-evoluer-ne-mourir/

Chavalarias, D. (2018, November 7). Fake news : l’arbre qui cache la forêt. AOC media - Analyse Opinion Critique. https://aoc.media/analyse/2018/11/07/fake-news-larbre-cache-foret/

Albert, S., Michl, M., Lunkenheimer, P., Loidl, A., Déjardin, P. M., & Ladieu, F. (2018). Third and Fifth Harmonic Responses in Viscous Liquids. In Nonlinear Dielectric Spectroscopy (pp. 219–260). Springer, Cham. https://doi.org/10.1007/978-3-319-77574-6_7

2017

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Vibert, J., & Thomas-Vaslin, V. (2017). Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background. PLOS Computational Biology, 13(3), e1005417. https://doi.org/10.1371/journal.pcbi.1005417

Thomas-Vaslin, V. (2017). Questionnements et connaissance de la complexité. Editions Matériologiques. https://hal.archives-ouvertes.fr/hal-01499478

Thomas-Vaslin, V. (2017). Le rôle des traces dans le système immunitaire : des anticorps au corps. (Paris CNRS éditions, Vol. 4). http://www.cnrseditions.fr/sociologie-ethnologie-anthropologie/7489-l-homme-trace.html%7D

Latapy, M., & Chavalarias, D. (2017). L’analyse à grande échelle de nos traces numériques. In M. Bouzeghoub & R. Mosseri (Eds.), Les Big Data à Découvert (CNRS Éditions).

Julien Delile, M. H., & Nadine Peyriéras, R. D. (2017). A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation. Nature Communication, 13929. https://doi.org/doi: 10.1038/ncomms13929

2016

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Villoutreix, P., Delile, J., Rizzi, B., Duloquin, L., Savy, T., Bourgine, P., Doursat, R., & Peyri’eras, N. (2016). An integrated modelling framework from cells to organism based on a cohort of digital embryos. Scientific Reports, 6, 37438. http://www.nature.com/articles/srep37438

Véronique Thomas-Vaslin, & Frédéric Jacquemart. (2016, Décembre). Approche de la résilience et perturbations des systèmes complexes par une évaluation globale. Congrès mondial pour la pensée complexe: Les défis d’un monde globalisé, Paris, France. https://hal.archives-ouvertes.fr/hal-01427233

Véronique Thomas-Vaslin, & Frédéric Jacquemart. (2016). L’évaluation globale des technologies. In La Fièvre de l’évaluation (Presses Universitaires du Septentrion, 2016, p. 196 p.). Bertrand Bocquet. https://hal.archives-ouvertes.fr/hal-01298219

Mathieu Le Goc, Lawrence H. Kim, Ali Parsaei, Jean-Daniel Fekete, Pierre Dragicevic, & Sean Follmer. (2016, October 16). Zooids: Building Blocks for Swarm User Interfaces. UIST ’16 Proceedings of the 29th Annual Symposium on User Interface Software and Technology, Tokyo, Japan. https://doi.org/10.1145/2984511.2984547

Kowaliw, T., & Doursat, R. (2016). Bias-variance decomposition in Genetic Programming. Open Mathematics, 14, 62–80. https://doi.org/http://doursat.free.fr/docs/Kowaliw_Doursat_2016_bvgp_OpenMath.pdf

Chavalarias, D., Wallach, J. D., Li, A. H. T., & Ioannidis, J. P. A. (2016). Evolution of Reporting P Values in the Biomedical Literature, 1990-2015. JAMA, 315(11), 1141. https://doi.org/10.1001/jama.2016.1952

Chavalarias, D. (2016). What’s wrong with Science? Scientometrics, 1–23. https://doi.org/10.1007/s11192-016-2109-9

Chavalarias, D. (2016). The unlikely encounter between von Foerster and Snowden: When second-order cybernetics sheds light on societal impacts of Big Data. Big Data & Society, 3(1), 2053951715621086. https://doi.org/10.1177/2053951715621086

Bouyrie, M., Cornuéjols, A., Manfredotti, C., & Peyriéras, N. (2016). Denoising 3D microscopy images of cell nuclei using shape priors on an anisotropic grid. Proc. of ICPRAM-2016. Int. Conf. on Pattern Recognition Applications and Methods, Rome, Italy.

Albert, S., Bauer, T., Michl, M., Biroli, G., Bouchaud, J.-P., Loidl, A., Lunkenheimer, P., Tourbot, R., Wiertel-Gasquet, C., & Ladieu, F. (2016). Fifth-order susceptibility unveils growth of thermodynamic amorphous order in glass-formers. Science, 352(6291), 1308–1311. https://doi.org/10.1126/science.aaf3182

2015

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2012

396913 DFIEKF27 2012 1 apa 50 creator desc 38346 https://iscpif.fr/wp-content/plugins/zotpress/

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Chavalarias, David, Cointet J-P., & Cornilleau L., Duong T-K, Mogoutov A., Villard L., Roth C., Savy T. (2011). Streams of Media Issues - Monitoring World Food Security. UN GLobal Pulse, Presented at United Nations, Oct.

Banos, A., & Thévenin, T. (Eds.). (2011). Geographical information and urban transport systems. ISTE ; Wiley.

2010

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Zanella, C., Campana, M., Rizzi, B., Melani, C., Sanguinetti, G., Bourgine, P., Mikula, K., Peyrieras, N., & Sarti, A. (2010). Cells Segmentation From 3-D Confocal Images of Early Zebrafish Embryogenesis. IEEE Transactions on Image Processing, 19(3), 770–781. https://doi.org/10.1109/TIP.2009.2033629

Roth, C., & Cointet, J.-P. (2010). Social and semantic coevolution in knowledge networks. Social Networks, 32(1), 16–29. https://doi.org/10.1016/j.socnet.2009.04.005

Reuillon, R., Chuffart, F., Leclaire, M., Faure, T., Dumoulin, N., & Hill, D. R. C. (2010). Declarative task delegation in OpenMOLE. In W. W. Smari & J. P. McIntire (Eds.), HPCS (pp. 55–62). IEEE. http://dblp.uni-trier.de/db/conf/ieeehpcs/ieeehpcs2010.html#ReuillonCLFDH10

Phan, D., & Varenne, F. (2010). Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting. Journal of Artificial Societies and Social Simulation, 13(1), 5. http://jasss.soc.surrey.ac.uk/13/1/5.html

Olivier, N., Luengo-Oroz, M. A., Duloquin, L., Faure, E., Savy, T., Veilleux, I., Solinas, X., Debarre, D., Bourgine, P., Santos, A., Peyrieras, N., & Beaurepaire, E. (2010). Cell Lineage Reconstruction of Early Zebrafish Embryos Using Label-Free Nonlinear Microscopy. Science, 329(5994), 967–971. https://doi.org/10.1126/science.1189428

Junier, I., Martin, O., & Képès, F. (2010). Spatial and Topological Organization of DNA Chains Induced by Gene Co-localization. PLoS Computational Biology, 6(2), e1000678. https://doi.org/10.1371/journal.pcbi.1000678

Junier, I., Herisson, J., & Kepes, F. (2010). Periodic pattern detection in sparse boolean sequences. Algorithms for Molecular Biology, 5(1), 31. https://doi.org/10.1186/1748-7188-5-31

Ginelli, F., Peruani, F., Bär, M., & Chaté, H. (2010). Large-Scale Collective Properties of Self-Propelled Rods. Physical Review Letters, 104(18). https://doi.org/10.1103/PhysRevLett.104.184502

Chavalarias, D., & Ioannidis, J. P. A. (2010). Science mapping analysis characterizes 235 biases in biomedical research. Journal of Clinical Epidemiology, 63(11), 1205–1215. https://doi.org/10.1016/j.jclinepi.2009.12.011

Baudrit, C., Sicard, M., Wuillemin, P. H., & Perrot, N. (2010). Towards a global modelling of the Camembert-type cheese ripening process by coupling heterogeneous knowledge with dynamic Bayesian networks. Journal of Food Engineering, 98(3), 283–293. https://doi.org/10.1016/j.jfoodeng.2009.12.012

Barthélemy, M., Nadal, J.-P., & Berestycki, H. (2010). Disentangling collective trends from local dynamics. Proceedings of the National Academy of Sciences, 107(17), 7629–7634. https://doi.org/10.1073/pnas.0910259107

2009

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Yang, H., Takeuchi, K. A., Ginelli, F., Chaté, H., & Radons, G. (2009). Hyperbolicity and the Effective Dimension of Spatially Extended Dissipative Systems. Physical Review Letters, 102(7). https://doi.org/10.1103/PhysRevLett.102.074102

Takeuchi, K. A., Ginelli, F., & Chaté, H. (2009). Lyapunov Analysis Captures the Collective Dynamics of Large Chaotic Systems. Physical Review Letters, 103(15). https://doi.org/10.1103/PhysRevLett.103.154103

Shuckburgh, E., d’Ovidio, F., & Legras, B. (2009). Local Mixing Events in the Upper Troposphere and Lower Stratosphere. Part II: Seasonal and Interannual Variability. Journal of the Atmospheric Sciences, 66(12), 3695–3706. https://doi.org/10.1175/2009JAS2983.1

Nicolau, M., & Schoenauer, M. (2009). On the evolution of scale-free topologies with a gene regulatory network model. Biosystems, 98(3), 137–148. https://doi.org/10.1016/j.biosystems.2009.06.006

Lavelle, C., Recouvreux, P., Wong, H., Bancaud, A., Viovy, J.-L., Prunell, A., & Victor, J.-M. (2009). Right-Handed Nucleosome: Myth or Reality? Cell, 139(7), 1216–1217. https://doi.org/10.1016/j.cell.2009.12.014

Lavelle, C. (2009). Forces and torques in the nucleus: chromatin under mechanical constraintsThis paper is one of a selection of papers published in this Special Issue, entitled 29th Annual International Asilomar Chromatin and Chromosomes Conference, and has undergone the Journal’s usual peer review process. Biochemistry and Cell Biology, 87(1), 307–322. https://doi.org/10.1139/O08-123

Junier, I., Mossa, A., Manosas, M., & Ritort, F. (2009). Recovery of Free Energy Branches in Single Molecule Experiments. Physical Review Letters, 102(7). https://doi.org/10.1103/PhysRevLett.102.070602

Institute of Electrical and Electronics Engineers (Ed.). (2009). IEEE INFOCOM 2009 - IEEE Conference on Computer Communications workshops: Rio de Janeiro, Brazil, 19 - 25 April 2009. IEEE.

Ginelli, F., Cencini, M., & Torcini, A. (2009). Synchronization of spatio-temporal chaos as an absorbing phase transition: a study in 2+1 dimensions. Journal of Statistical Mechanics: Theory and Experiment, 2009(12), P12018. https://doi.org/10.1088/1742-5468/2009/12/P12018

El Boustani, S., Marre, O., Béhuret, S., Baudot, P., Yger, P., Bal, T., Destexhe, A., & Frégnac, Y. (2009). Network-State Modulation of Power-Law Frequency-Scaling in Visual Cortical Neurons. PLoS Computational Biology, 5(9), e1000519. https://doi.org/10.1371/journal.pcbi.1000519

d’Ovidio, F., Isern-Fontanet, J., López, C., Hernández-García, E., & García-Ladona, E. (2009). Comparison between Eulerian diagnostics and finite-size Lyapunov exponents computed from altimetry in the Algerian basin. Deep Sea Research Part I: Oceanographic Research Papers, 56(1), 15–31. https://doi.org/10.1016/j.dsr.2008.07.014

d’Ovidio, F., Shuckburgh, E., & Legras, B. (2009). Local Mixing Events in the Upper Troposphere and Lower Stratosphere. Part I: Detection with the Lyapunov Diffusivity. Journal of the Atmospheric Sciences, 66(12), 3678–3694. https://doi.org/10.1175/2009JAS2982.1

D’Ovidio, F., Taillandier, V., Mortier, L., & Taupier-Letage, I. (2009). Lagrangian validation of the Mediterranean mean dynamic topography by extraction of tracer frontal structures. Mercator Ocean Q. Newslett, 32, 24Á32.

Banos, A., & Paré, A. (2009). Simuler les déplacements de piétons dans une station de métro Une approche à base d’agents. Revue Internationale de Géomatique, 19(3), 277–302. https://doi.org/10.3166/geo.19.277-302

Bailly, F., & Longo, G. (2009). BIOLOGICAL ORGANIZATION AND ANTI-ENTROPY. Journal of Biological Systems, 17(01), 63–96. https://doi.org/10.1142/S0218339009002715

2008

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Spicher, A., Michel, O., Cieslak, M., Giavitto, J.-L., & Prusinkiewicz, P. (2008). Stochastic P systems and the simulation of biochemical processes with dynamic compartments. Biosystems, 91(3), 458–472. https://doi.org/10.1016/j.biosystems.2006.12.009

Roth, C., Obiedkov, S., & Kourie, D. G. (2008). ON SUCCINCT REPRESENTATION OF KNOWLEDGE COMMUNITY TAXONOMIES WITH FORMAL CONCEPT ANALYSIS. International Journal of Foundations of Computer Science, 19(02), 383–404. https://doi.org/10.1142/S0129054108005735

Roth, C. (2008). Coévolution des auteurs et des concepts dans les réseaux épistémiques : le cas de la communauté « zebrafish». Revue française de sociologie, 49(3), 523. https://doi.org/10.3917/rfs.493.0523

Peruani, F., Deutsch, A., & Bär, M. (2008). A mean-field theory for self-propelled particles interacting by velocity alignment mechanisms. The European Physical Journal Special Topics, 157(1), 111–122. https://doi.org/10.1140/epjst/e2008-00634-x

Peruani, F., & Sibona, G. J. (2008). Dynamics and Steady States in Excitable Mobile Agent Systems. Physical Review Letters, 100(16). https://doi.org/10.1103/PhysRevLett.100.168103

Mitra, B., Ghose, S., Ganguly, N., & Peruani, F. (2008). Stability analysis of peer-to-peer networks against churn. Pramana, 71(2), 263–273. https://doi.org/10.1007/s12043-008-0159-0

Jensen, P., Rouquier, J.-B., Kreimer, P., & Croissant, Y. (2008). Scientists who engage with society perform better academically. Science and Public Policy, 35(7), 527–541. https://doi.org/10.3152/030234208X329130

Hoelzer, G. A., Drewes, R., Meier, J., & Doursat, R. (2008). Isolation-by-Distance and Outbreeding Depression Are Sufficient to Drive Parapatric Speciation in the Absence of Environmental Influences. PLoS Computational Biology, 4(7), e1000126. https://doi.org/10.1371/journal.pcbi.1000126

Giavitto, J.-L., & Spicher, A. (2008). Topological rewriting and the geometrization of programming. Physica D: Nonlinear Phenomena, 237(9), 1302–1314. https://doi.org/10.1016/j.physd.2008.03.039

Fuchs, J., Schelter, J., Ginelli, F., & Hinrichsen, H. (2008). Local persistence in the directed percolation universality class. Journal of Statistical Mechanics: Theory and Experiment, 2008(04), P04015. http://stacks.iop.org/1742-5468/2008/i=04/a=P04015

Doursat, R., & Ulieru, M. (2008). Emergent engineering for the management of complex situations. In A. Manzalini (Ed.), Autonomics (p. 14). ICST. http://dblp.uni-trier.de/db/conf/autonomics/autonomics2008.html#DoursatU08

Doursat, R. (2008). Organically Grown Architectures: Creating Decentralized, Autonomous Systems by Embryomorphic Engineering. In Organic Computing (pp. 167–199). Springer Berlin Heidelberg. http://dx.doi.org/10.1007/978-3-540-77657-4_8

Chavalarias, David, & Cointet, Jean-Philippe. (2008). Multi-level Science mapping with asymmetric co-occurrence analysis: Methodology and case study. Networks and Heterogeneous Media, 267–276.

Chavalarias, D., & Cointet, J.-P. (2008). Bottom-up scientific field detection for dynamical and hierarchical science mapping, methodology and case study. Scientometrics, 75(1), 37–50. https://doi.org/10.1007/s11192-007-1825-6

Chaté, H., Ginelli, F., Grégoire, G., & Raynaud, F. (2008). Collective motion of self-propelled particles interacting without cohesion. Physical Review E, 77(4). https://doi.org/10.1103/PhysRevE.77.046113

Chaté, H., Ginelli, F., Grégoire, G., Peruani, F., & Raynaud, F. (2008). Modeling collective motion: variations on the Vicsek model. The European Physical Journal B, 64(3–4), 451–456. https://doi.org/10.1140/epjb/e2008-00275-9

2007

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Takeuchi, K. A., Kuroda, M., Chaté, H., & Sano, M. (2007). Directed Percolation Criticality in Turbulent Liquid Crystals. Physical Review Letters, 99(23). https://doi.org/10.1103/PhysRevLett.99.234503

Spicher, A., & Michel, O. (2007). Declarative modeling of a neurulation-like process. Biosystems, 87(2–3), 281–288. https://doi.org/10.1016/j.biosystems.2006.09.024

Roth, C. (2007). Empiricism for descriptive social network models. Physica A: Statistical Mechanics and Its Applications, 378(1), 53–58. https://doi.org/10.1016/j.physa.2006.11.045

Ginelli, F., Poggi, P., Turchi, A., Chaté, H., Livi, R., & Politi, A. (2007). Characterizing Dynamics with Covariant Lyapunov Vectors. Physical Review Letters, 99(13). https://doi.org/10.1103/PhysRevLett.99.130601

Chaté, H., Ginelli, F., & Grégoire, G. (2007). Comment on “Phase Transitions in Systems of Self-Propelled Agents and Related Network Models.” Physical Review Letters, 99(22). https://doi.org/10.1103/PhysRevLett.99.229601

2006

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Shalizi, C. R., Haslinger, R., Rouquier, J.-B., Klinkner, K. L., & Moore, C. (2006). Automatic filters for the detection of coherent structure in spatiotemporal systems. Physical Review E, 73(3). https://doi.org/10.1103/PhysRevE.73.036104

Chavalarias, D. (2006). Metamimetic Games: Modeling Metadynamics in Social Cognition. Journal of Artificial Societies and Social Simulation, 9(2), 5. http://jasss.soc.surrey.ac.uk/9/2/5.html

Chaté, H., Ginelli, F., & Montagne, R. (2006). Simple Model for Active Nematics: Quasi-Long-Range Order and Giant Fluctuations. Physical Review Letters, 96(18). https://doi.org/10.1103/PhysRevLett.96.180602

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