VILAR LAB

CONTACT

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Degrees 

• 1995: B.S./M.S. in Physics, University of Barcelona
• 1998: Ph.D. in Physics, University of Barcelona               
  

Appointments

• 1996-1998: Predoctoral Research Fellow,  Department of Fundamental Physics, University of Barcelona
• 1998-2000: Postdoctoral Research Fellow, Departments of Physics and Molecular Biology, Princeton University
• 2000-2001: Research Associate, Howard Hughes Medical Institute, Department of Molecular Biology, Princeton University
• 2001-2003: Postdoctoral Associate, The Rockefeller University
• 2004-2008: Head of Laboratory & Assistant Member, Computational Biology Program, Sloan-Kettering Institute, Memorial Sloan-Kettering Cancer Center
• 2005-2008: Assistant Professor of Physiology, Biophysics, and Systems Biology, Weill Graduate School of Medical Sciences, Cornell University
• 2008-Present: Ikerbasque Professor, Biofisika Institute (CSIC-UPV/EHU), University of the Basque Country

Honors and Awards

• 
  Winner of the European Union Big Data Technologies Horizon Prize (ec.europa.eu/research/horizonprize/index.cfm?pg=prizes)
• "Highlights of the Year 2014" (physics.aps.org/articles/v7/132) by the American Physical Society to "Entropy of leukemia on multidimensional morphological and molecular landscapes" [Phys. Rev. X 4, 21038 (2014)]
• Awarded "Best of 2013" by the Biophysical Society to the article "Systems Biophysics of Gene Expression" [Biophys. J. 104, 2574-2585 (2013)]
• 2012 Werfen-Izasa-Beckman-Coulter prize in Biophysics
• Best performer (Team team21) at the DREAM6/FlowCAP2 Molecular Classification of Acute Myeloid Leukaemia Challenge ( www.synapse.org/#!Synapse:syn2887788/wiki/72181)

Selected Review Panels

• Member of the panel Computer Science and Informatics (PE6), Advanced Grant 2021, European Research Council (ERC), November 2021 & February 2022, Brussels (Belgium).
• Member of the panel Computer Science and Informatics (PE6), Advanced Grant 2019, European Research Council (ERC), November 2019 & February 2020, Brussels (Belgium).
• Member of the panel Computer Science and Informatics (PE6), Advanced Grant 2017, European Research Council (ERC), November 2017 & February 2018, Brussels (Belgium).
• Participant in the 2016 expert review panel conducted by The National Cancer Institute (NCI) Division of Cancer Biology (DCB) to assess the impact and innovativeness of research funded by NCI's Physical Sciences - Oncology Centers (PS-OC) Program, NCI's Integrative Cancer Biology Program (ICBP), and NCI R01 awards.
• Member of the panel Computer Science and Informatics (PE6), Advanced Grant 2015, European Research Council (ERC), September 2015 & January 2016, Brussels (Belgium).
• Member of the 2009 Scientific Review Panel on Physical Sciences-Oncology Centers (U54), National Cancer Institute/National Institutes of Health, June 2009, Bethesda (Maryland, USA).
• Member of the 2007 and 2008 Scientific Review Panels of the New Jersey Commission on Cancer Research, Princeton (New Jersey, USA).

Editorial

• 2021-Present: Associate Editor, Frontiers in Systems Biology
• 2021-Present: Editorial Board Member, Foundations
• 2020-Present: Editorial Board Member, Biology
• 2017-Present: Advisory Editor, European Biophysics Journal
• 2015-2022: Academic Editor, PLoS ONE
• 2014: Ad hoc Associate Editor, Physical Review X
• 2012-Present: Editorial Board Member, In Silico Biology
• 2008-2019: Associate Editor, BMC Systems biology
• 2007: Ad hoc Divisional Associate Editor, Physical Review Letters

The traditional experimental approach to the study of the functioning of cells has been remarkably successful at identifying cellular components and their interactions. Current automated technologies have brought the cartoon-like representations of cellular processes to exponentially growing webs of nodes and links that seem as close to completion as ever. The complexity of the emerging picture, however, makes it clear that all this information by itself is not enough to truly understand processes such as cancer. In order to piece back together all the genetic, biochemical, molecular, and structural information into a physiologically relevant description of the cell, one needs "constructive" methods. Computational modeling has emerged as a promising tool for transforming molecular detail into a more integrated form of understanding complex behavior.

We use computational and mathematical modeling to study biological networks that are relevant to cancer. We are interested, not only in the interactions between cellular components, but also in the resulting cellular behavior and its integration into the physiological context of an organism. We study computationally how mutations affect the molecular properties of the cellular components; how the mutated components affect different pathways; and how these modified pathways confer cell-growth advantages during tumor progression and metastasis. Having a global view of all these processes and their effects through all relevant levels of biological organization is crucial to identify and characterize the key control elements of the system.

We are currently working on:

• Gene regulation (RXR and other nuclear hormone receptors)
• Signal transduction (EGF and TGF-β pathways)
• Control of cell growth and death (Bcl-2/Bax in metabolism and apoptosis)

We are also developing new computational approaches to determine, capture, and use the relevant biological information. We are especially interested in stochastic analyses and in multilevel and multiscale methods.

Press on our research

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Open Source Software

• J. M. G. Vilar and L. Saiz (2019), Scaling and Regression over Nearest Neighbors for Single-Cell Signaling Prediction in Breast Cancer, https://www.synapse.org/#!Synapse:syn21188145
• J. M. G. Vilar (2018), Data-driven prediction of electricity grid traffic (winner solution of the European Union Big Data Technologies Horizon Prize https://ec.europa.eu/research/horizonprize/index.cfm?prize=bigdata). Repository available at https://github.com/jmgvilar/H2020BigDataPrize/
• J. M. G. Vilar and L. Saiz (2017), Combined ridge, support-vector, and random-forest regression approach for odor prediction, https://www.synapse.org/#!Synapse:syn3794504
• J. M. G. Vilar (2014), Predicting the overall survival time of AML patients using marginal probability ratios, https://www.synapse.org/#!Synapse:syn2702223
• J. M. G. Vilar (2014), Predicting remission duration in AML patients with Complete Remission using marginal probability ratios, https://www.synapse.org/#!Synapse:syn2702224
• J. M. G. Vilar (2014), Predicting Complete Remission or Primary Resistance in AML patients using marginal probability ratios, https://www.synapse.org/#!Synapse:syn2702225
• "CplexA" (released on April 19th, 2010/updated on December 12th, 2012) is a software package (available for Mathematica, Python, and Matlab) to compute probabilities and average properties of macromolecular assembly and its effects in gene regulation. CplexA and the tutorial are available at https://sourceforge.net/projects/cplexa/

Preprints

• J. M. G. Vilar, J. M. Rubi, and L. Saiz, Chaperone-driven entropic separation of amyloid nanofilament bundles, bioRxiv 2023.05.24.542046; doi: https://doi.org/10.1101/2023.05.24.542046 (2023).
• J. M. G. Vilar and L. Saiz, The unreasonable effectiveness of equilibrium gene regulation through the cell cycle, bioRxiv 2023.03.31.535089; doi: https://doi.org/10.1101/2023.03.31.535089 (2023).
• J. M. G. Vilar, Winning the Big Data Technologies Horizon Prize: Fast and reliable forecasting of electricity grid traffic by identification of recurrent fluctuations, arXiv:1902.04337 (2019).

Articles in journals

• J. M. G. Vilar and L. Saiz, Multi-landmark alignment of genomic signals reveals conserved expression patterns across transcription start sites, Scientific Reports 13: 10835 (2023).
• J. M. G. Vilar and L. Saiz, Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time series, Science Advances 9, eadf0673 (2023).
• C. Chang, M. Garcia-Alcala, L. Saiz, J. M. G. Vilar, and P. Cluzel, Robustness of DNA Looping Across Multiple Cell Divisions in Individual Bacteria, Proc. Natl. Acad. Sci. USA 119, e2200061119 (2022).
• J. M. G. Vilar and L. Saiz, Ascertaining the initiation of epidemic resurgences: an application to the COVID-19 second surges in Europe and the Northeast United States, Royal Society Open Science 10, 210773 (2021).
• A. Franco, P. Gracia, A. Colom, J. D. Camino, J. A. Fernandez-Higuero, N. Orozco, A. Dulebo, L. Saiz, N. Cremades, J. M. G. Vilar, A. Prado, A. Muga, All-or-none amyloid disassembly via chaperone-triggered fibril unzipping favors clearance of α-synuclein toxic species, Proc. Natl. Acad. Sci. USA 118, e2105548118 (2021).
• J. M. G. Vilar and L. Saiz, Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data, Scientific Reports 11, 19952 (2021).
• A. Gabor, M. Tognetti, A. Driessen, J. Tanevski, B. Guo, W. Cao, H. Shen, T. Yu, V. Chung, Single Cell Signaling in Breast Cancer DREAM Consortium (*), Bernd Bodenmiller, Julio Saez-Rodriguez (* including J. M. G. Vilar), Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd, Molecular Systems Biology 17, e10402 (2021).
• J. A. Fernandez-Higuero, A. Muga, J. M. G. Vilar, Extraction and Refolding Determinants of Chaperone-Driven Aggregated Protein Reactivation, J. Mol. Biol. 432, 3239-3250 (2020).
• Y. Cabrera, L. Dublang, J. A. Fernandez-Higuero, D. Albesa-Jove, M. Lucas, A. R. Viguera, M. E. Guerin, J. M. G. Vilar, A. Muga, F. Moro, Regulation of human Hsc70 ATPase and chaperone activities by Apg2: role of the acidic subdomain, J. Mol. Biol. 431, 444-461 (2019).
• M. L. Fanani, J. V. Busto, J. Sot, J. Abad, G. Fabrias, L. Saiz, J. M. G. Vilar, F. M. Goni, B. Maggio, and A. Alonso, Clearly Detectable, Kinetically Restricted Solid-Solid Phase Transition in cis-Ceramide Monolayers, Langmuir 34, 11749-11758 (2018).
• J. M. G. Vilar and J. M. Rubi, Determinants of population responses to environmental fluctuations, Scientific Reports 8: 887 (2018).
• J. M. G. Vilar and L. Saiz, Computing at the front-end by receptor networks, Cell Systems 5, 316-318 (2017).
• A. Keller, R.C. Gerkin, Y. Guan, A. Dhurandhar, G. Turu, B. Szalai, J.D. Mainland, Y. Ihara, C.W. Yu., R. Wolfinger, C. Vens, L. Schietgat, K. De Grave, R. Norel, DREAM Olfaction Prediction Consortium (*), G. Stolovitzky, G.A. Cecchi, L.B. Vosshall, P. Meyer (* including J.M.G. Vilar), Predicting human olfactory perception from chemical features of odor molecules, Science 355, 820-826 (2017).
• D.P. Noren, B.L. Long, R. Norel, K. Rrhissorrakrai, K. Hess, C.W. Hu, A.J. Bisberg, A. Schultz, E. Engquist, L. Liu, X. Lin, G.M. Chen, H. Xie, G.A.M. Hunter, P.C. Boutros, O. Stepanov, DREAM 9 AML-OPC Consortium (*), T. Norman, S.H. Friend, G. Stolovitzky, S. Kornblau, A.A. Qutub (* including J.M.G. Vilar), A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis, PLoS Comput. Biol. 12: e1004890 (2016).
• J. M. G. Vilar and L. Saiz, Suppression and enhancement of transcriptional noise by DNA looping, Phys. Rev. E 89, 062703 (2014).
• J. M. G. Vilar, Entropy of Leukemia on Multidimensional Morphological and Molecular Landscapes, Phys. Rev. X 4, 021038 (2014).
• J. M. G. Vilar and J. M. Rubi, Communication: System-size scaling of Boltzmann and alternate Gibbs entropies, J. Chem. Phys. 140, 201101 (2014).
• J. M. G. Vilar and L. Saiz, Systems Biophysics of Gene Expression, Biophys. J. 104, 2574-2585 (2013).
• J. M. G. Vilar and L. Saiz, Reliable prediction of complex phenotypes from a modular design in free energy space: an extensive exploration of the lac operon, ACS Synth. Biol. 2, 576-586 (2013).
• N. Aghaeepour, G. Finak, The FlowCAP Consortium, The DREAM Consortium (*), H. Hoos, T.R. Mosmann, R. Brinkman, R. Gottardo, and R.H. Scheuermann (* including J. M. G. Vilar), Critical assessment of automated flow cytometry data analysis techniques, Nature Methods 10, 228-238 (2013). Supplementary Information [pdf].
• J. M. G. Vilar and J. M. Rubi, Far-from-equilibrium processes without net thermal exchange via energy sorting, J. Chem. Phys. 136, 064115 (2012).
• J. M. G. Vilar and L. Saiz, Trafficking Coordinate Description of Intracellular Transport Control of Signaling Networks, Biophys. J. 101, 2315-2323 (2011).
• J. M. G. Vilar and L. Saiz, Control of gene expression by modulated self-assembly, Nucleic Acids Research 39, 6854-6863 (2011).
• J. M. G. Vilar and J. M. Rubi, Work-Hamiltonian connection for anisoparametric processes in manipulated microsystems, J. Non-Equilib. Thermodyn. 36, 123-130 (2011).
• N. Geisel, J. M. G. Vilar, and J. M. Rubi, Optimal Resting-Growth Strategies of Microbial Populations in Fluctuating Environments, PLoS One 6, e18622 (2011).
• J. M. G. Vilar, Noisy-threshold control of cell death, BMC Systems Biology 4, 152 (2010).
• J. M. G. Vilar, Accurate Prediction of Gene Expression by Integration of DNA Sequence Statistics with Detailed Modeling of Transcription Regulation, Biophys. J. 99, 2408-2413 (2010).
• J. M. G. Vilar and L. Saiz, CplexA: a Mathematica package to study macromolecular-assembly control of gene expression, Bioinformatics 26, 2060-2061 (2010). Supplementary Information: Supplementary Data files 1 [pdf] and 2 [nb].
• L. Saiz and J. M. G. Vilar, Protein-protein/DNA interaction networks: versatile macromolecular structures for the control of gene expression, IET Systems Biology 2, 247-255 (2008).
• J. M. G. Vilar and J. M. Rubi, Failure of the Work-Hamiltonian Connection for Free-Energy Calculations, Phys. Rev. Lett. 100, 020601 (2008).
• L. Saiz and J. M. G. Vilar, Ab initio thermodynamic modeling of distal multisite transcription regulation, Nucleic Acids Research 36, 726-731 (2008).
• M. H. Vainstein, J. M. Rubi and J. M. G. Vilar, Stochastic population dynamics in turbulent fields, Eur. Phys. J. ST 146, 177-187 (2007).
• L. Saiz and J. M. G. Vilar, Multilevel deconstruction of the in vivo behavior of looped DNA-protein complexes, PLoS One 2, e355 (2007).
• W. Y. Shou, S. Ram, and J. M. G. Vilar, Synthetic cooperation in engineered yeast populations, Proc. Natl. Acad. Sci. USA 104, 1877-1882 (2007).
• J. M. G. Vilar and L. Saiz, Multiprotein DNA looping, Phys. Rev. Lett. 96, 238103 (2006).
• L. Saiz and J. M. G. Vilar, DNA looping: the consequences and its control, Curr. Opin. Struct. Biol. 16, 344-350 (2006).
• L. Saiz and J. M. G. Vilar, Stochastic dynamics of macromolecular-assembly networks,  Molecular Systems Biology 2, 0024 (2006).
• J. M. G. Vilar, Modularizing gene regulation, Molecular Systems Biology 2, 0016 (2006).
• J. M. G. Vilar, R. Jansen, and C. Sander, Signal processing in the TGF-β superfamily ligand-receptor network, PLoS Comput. Biol. 2, e3 (2006).
• L. Saiz, J. M. Rubi, and J. M. G. Vilar, Inferring the in vivo looping properties of DNA, Proc. Natl. Acad. Sci. USA 102, 17642-17645 (2005).
• D. Reguera, J. M. Rubi, and J. M. G. Vilar, The Mesoscopic Dynamics of Thermodynamic Systems, J. Phys. Chem. B 109, 21502-21515 (2005).
• J. M. G. Vilar and L. Saiz, DNA looping in gene regulation: From the assembly of macromolecular complexes to the control of transcriptional noise, Curr. Opin. Genet. Dev. 15, 136-144 (2005).
• E. Korobkova, T. Emonet, J. M. G. Vilar, T. S. Shimizu, P. Cluzel, From molecular noise to behavioural variability in a single bacterium, Nature 428, 574-578 (2004). 
• J. M. G. Vilar and S. Leibler, DNA looping and physical constrains on transcription regulation, J. Mol. Biol. 331, 981-989 (2003).
•  J. M. G. Vilar, C. C. Guet, and S. Leibler, Modeling network dynamics: the lac operon, a case study, J. Cell Biol. 161, 471-476 (2003).
• J. M. G. Vilar, R. V. Sole, and J. M. Rubi, On the origin of plankton patchiness, Physica A 317, 239-246 (2002).
• Jose M. G. Vilar, Hao Yuan Kueh, Naama Barkai, and Stanislas Leibler, Mechanisms of noise-resistance in genetic oscillators, Proc. Natl. Acad. Sci. USA 99, 5988-15992 (2002). 
• J. M. G. Vilar and J. M. Rubi, Thermodynamics "beyond" local equilibrium,  Proc. Natl. Acad. Sci. USA 98, 11081-11084 (2001). 
• J. M. G. Vilar and J. M. Rubi, Noise suppression by noise, Phys. Rev. Lett. 86, 950-953 (2001). 
• L. Saiz, J. M. G. Vilar, and J. M. Rubi, Field-induced force-suppression in ferromagnetic colloids, Physica A 293, 51-58 (2001).
• J. M. G. Vilar and J. M. Rubi, Ordering periodic spatial structures by non-equilibrium fluctuations, Physica A 277, 327-334 (2000).
• J. M. Rubi and J. M. G. Vilar, The Rheology of Field-Responsive Suspensions, J. Phys.: Cond. Matter  12, A75-A84 (2000).
• A. Perez-Madrid, T. Alarcon, J.M.G. Vilar, and J. M. Rubi, Mesoscopic Approach to the "Negative'' Viscosity Effect in Ferrofluids, Physica A 270, 403-412 (1999).
• J. M. G. Vilar, R. V. Sole, and J. M. Rubi, Noise and Periodic Modulations in Neural Excitable Media, Phys. Rev. E  59, 5920-5928 (1999).
• J. M. G. Vilar and J. M. Rubi, Scaling Concepts in Periodically Modulated Noisy Systems, Physica A 264, 1-14 (1999).
• J. M. G. Vilar, G. Gomila and J. M. Rubi, Stochastic Resonance in Noisy Nondynamical Systems, Phys. Rev. Lett. 81, 14-17 (1998).
• J. M. G. Vilar and R. V. Sole, Effects of Noise in Symmetric Two-Species Competition, Phys. Rev. Lett. 80, 4099-4102 (1998).
• J. M. G. Vilar and J. M. Rubi, Effect of the Output of the System in Signal Detection, Phys. Rev. E 56, 32R-35R (1997).
• J. M. G. Vilar and J. M. Rubi, Stochastic Multiresonance, Phys. Rev. Lett. 78, 2882-2885 (1997). 
• J. M. G. Vilar and J. M. Rubi, Spatiotemporal Stochastic Resonance in the Swift-Hohenberg Equation, Phys. Rev. Lett. 78, 2886-2889 (1997).
• Jose M. Gomez-Vilar and Ricard V. Sole, On cellular automata models for quantum systems, J. Phys. A 29, 8169 -8171 (1996).
• J. M. G. Vilar, A. Perez-Madrid, and J. M. Rubi, Stochastic Resonance in a Dipole, Phys. Rev. E 54, 6929-6932 (1996).
• J. M. G. Vilar and J. M. Rubi, Divergent Signal-to-Noise Ratio and Stochastic Resonance in Monostable Systems, Phys. Rev. Lett. 77, 2863-2866 (1996).

Book chapters

• J. M. G. Vilar and J. M. Rubi, Scaling of Noise and Constructive Aspects of Fluctuations, in Lecture Notes in Physics: "Stochastic Processes in Physics", J. Freund and T. Poschel, eds., Springer Verlag (Berlin, Heidelberg 2000), Vol. 557: pp. 121-130 (2000).

Books

D. Reguera, J. M. G. Vilar, and J. M. Rubi (eds.), Statistical Mechanics of Biocomplexity, Lecture Notes in Physics (Springer Verlag, Berlin 1999).

Selected invited talks

• Dynamics-informed characterization of molecular, cellular, and population mechanisms. SEB Centenary Conference 2023, July 2023, Edinburg (UK).
  
• Inverting convolutional neural networks for super-resolution identification of regime changes in epidemiological time series. Belgrade BioInformatics Conference 2023, June 2023, Belgrade (Serbia).
  
• Entropic separation of nanofilament bundles, XXVII Sitges Conference on Statistical Mechanics: Nonequilibrium Phenomena: from Quantum to Macroscopic Scales , May 2023, Sitges, Barcelona (Spain).
  
• Dynamics-informed characterization of molecular, cellular, and population mechanisms, Workshop on Dynamic Modeling and Statistical Inference in the Life Sciences, November 2022, Bilbao (Spain).
  
• Inference and prediction in biological systems at the molecular, cellular, and cell-population levels, Basel Computational Biology Seminar Series , October 2019, Basel (Switzerland).
  
• Predicting non-equilibrium fluctuations: from single molecules to country-wide electric grids, XXVI Sitges Conference on Statistical Mechanics: New Trends in Statistical Physics , May 2019, Sitges, Barcelona (Spain).
  
• Presentation of the winner solution of the European Union Big Data Technologies Horizon Prize. European Big Data Value Forum 2018, November 2018, Vienna (Austria).
  
• Inference and prediction in molecular biological systems. Belgrade BioInformatics Conference 2018, June 2018, Belgrade (Serbia).
  
• Prediction and inference in complex biophysical systems, 6th International Iberian Congress of Biophysics / X Iberoamerican Congress of Biophysics, June 2018, Castellon (Spain).
  
• Biophysical and Biomedical Applications of the Gibbs Entropy Postulate, Entropy 2018: From Physics to Information Sciences and Geometry, May 2018, Barcelona (Spain).
  
• Computational systems biophysics of cellular processes in health and disease. Belgrade BioInformatics Conference 2016, June 2016, Belgrade (Serbia).
  
• Automated diagnosis of leukemia. Biomedical Engineering Society Annual Meeting, October 2015, Tampa (Florida).
  
• Gene expression and long-range cooperativity on DNA. Advanced Workshop on Interdisciplinary Views on Chromosome Structure and Function, September 2014, Trieste (Italy).
• Gibbs entropy postulate: from thermodynamics "beyond" local equilibrium to biomedical applications. XXIV Sitges Conference on Statistical Mechanics: New Horizons in Statistical Physics and its Applications, June 2014, Barcelona (Spain).
  
• Systems biophysics of gene expression.  9th European Biophysics Congress, July 2013, Lisbon (Portugal).
  
• Computational biophysics of cellular processes in health and disease. International Congress of the Spanish Biophysical Society – SBE Barcelona 2012, July 2012, Barcelona (Spain).
  
• Submicron-scale statistical thermodynamics in living systems. XXIII Sitges Conference on Statistical Mechanics: Understanding and Managing Randomness in Physics, Chemistry and Biology, June 2012, Sitges, Barcelona (Spain).
• Computational systems biophysics at the molecular, cellular, and cell-population levels. National Cancer Institute (NCI) and National Science Foundation (NSF) international Assessment of Physical Sciences and Engineering Advances in Life Sciences and Oncology, May 2012, Barcelona (Spain).
  
• Multidimensional entropies for diagnosing Acute Myeloid Leukemia from patient samples using flow cytometry data, DREAM-RECOMB annual meeting, October 2011, Barcelona (Spain).
  
• Signal processing in the TGF-β superfamily ligand-receptor network. Systems Biology and Connective Tissue Disorders Meeting, February 2011, Washington, DC.
  
• From components to systems: lessons from gene regulation and synthetic cooperation. 1st colloquium of the Systems and Synthetic Biology Program of the CNB, November 2010, Madrid (Spain).
• Noise propagation across molecular, cellular, and cell-population scales. Noise in Life 2010, October 2010, Benasque (Spain).
• Noise propagation across molecular, cellular, and cell-population scales. Timing and Dynamics in Biological Systems, September 2010, Dresden (Germany).
  
• The logics of macromolecular assembly. Information Processing in Cells and Tissues: From small scale dynamics to understanding systems behavior, April 2009, Ascona (Switzerland).
  
• Intracellular noise and long-range interactions on DNA. Spatial 2009, Overcoming Distance in Signaling Networks, March 2009, Maale HaChamisha (Israel).
  
• From components to systems and vice versa: lessons from gene regulation and synthetic cooperation. Workshop on Cellular Decision Making, June 2008, Toronto (Canada).
• Signal processing in the TGF-β superfamily ligand-receptor network. Conference on Systems Biology of Mammalian Cells, May 2008, Dresden (Germany).
• Stochastic dynamics of protein-DNA complexes. Workshop on Deconstructing Biochemical Networks, September 2007, Montreal (Canada).
• Stochastic dynamics of protein-DNA complexes. Information Processing in Cellular Signaling and Gene Regulation, August 2007, Santa Fe (New Mexico).
• Inferring the in vivo looping properties of DNA. Third international conference on Multiscale Materials Modeling, September 2006, Freiburg (Germany).
• Computational Modeling of the TGF-β Superfamily Ligand-Receptor Network. British Society for Developmental Biology Autumn Meeting: Signal Transduction and Integration in Embryonic Development, Sept 2006, Dundee (UK).
• Stochastic dynamics of protein-DNA complexes. Workshop on Nanomechanics of Biomolecules, August 2006, Ascona (Switzerland).
• Macromolecular assembly on looped DNA. ICAM workshop on "Chromatin Dynamics, Gene Regulation and Silencing", August 2006, Snowmass (Colorado).
• Stochastic Dynamics of Macromolecular-Assembly Networks. XX Sitges Conference on Statistical Mechanics. Physical Biology: from Molecular Interactions to Cellular Behavior, June 2006, Sitges, Barcelona (Spain). 
• Stochastic Dynamics of Macromolecular-Assembly Networks. Systems Biology Discussion Group, New York Academy of Sciences, November 2005, New York (New York). 
• Stochastic Dynamics of Macromolecular-Assembly Networks. ISQBP Gilda Loew Memorial Meeting, October 2005, Staten Island (New York).
• Mechanisms of Noise-resistance in Genetic Oscillators. SIAM Conference on the Life Sciences, July 2004, Portland (Oregon).
• Mathematical analysis of gene circuits. Conference on Mathematical Modelling of Plant Development and Gene Networks, University of Warwick, May 2004, Coventry (United Kingdom).
• Modeling the Networks of the Cell: Molecular, Cellular, and Population Levels. Workshop on Biological Information and Statistical Physics, July 2003, Dresden (Germany).
• Modeling Noise, Switches and Clocks. Workshop on Dynamics, Adaptation and Fluctuations in Bio-networks, KITP, University of California, March 2003, Santa Barbara (California).
• Noise in the cell: from molecular mechanisms to populations via network design. Annual American Physical Society March Meeting, March 2002, Indianapolis (Indiana).
• Networking with noise at the molecular, cellular, and population level. Gordon Research Conference on Bioinformatics: From inference to Predictive Models, August 2001, Tilton (New Hampshire).
• Modules of modules: from molecular interactions to cell populations. Workshop on Design and Control of Biochemical Networks, June 2001, Leiden (The Netherlands).
• Ordering Periodic Spatial Structures by Noise. Workshop on Fluctuations Far From Equilibrium: Noise Induced Transport, April 1998, Dresden (Germany).

People

Current

Jose Vilar (Ikerbasque Professor)

Want to join? See opportunities below!

Former (VILARlab at Memorial Sloan-Kettering Cancer Center, 2004-2008)

Leonor Saiz (Visiting Investigator, 2004-2007)

Wenying Shou (Postdoc, 2006-2007)

Anamika Sarkar (Postdoc, 2004-2005)

Ori Weitz (Rotation Student, Tri-i CBM program, 2006)
Pawel Kocieniewski (Rotation Student, Tri-i CBM program, 2007)
Fan Xia (Rotation Student, PBSB program, 2007)
Ricky Chachra (Rotation Student, PBSB program, 2008)
Igor Segota (Rotation Student, PBSB program, 2008)

Opportunities

There are openings for Graduate Students and Postdoctoral Researchers. To apply please contact Jose Vilar at