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Journal papers


  • [Lilienthal et al., 2017] Lilienthal, S., Klein, M., Orbach, R., Willner, I., Remacle, F., and Levine, R. (2017). Continuous variables logic via coupled automata using a dnazyme cascade with feedback. Chemical Science.


  • [Colliaux et al., 2016] Colliaux, D., Bessière, P., and Droulez, J. (2016). Cell signaling as a probabilistic computer. International Journal of Approximate Reasoning.
  • [Coninx et al., 2016] Coninx, A., Bessière, P., and Droulez, J. (2016). Quick and energy-efficient bayesian computing of binocular disparity using stochastic digital signals. International Journal of Approximate Reasoning.
  • [Faix et al., 2016] Faix, M., Laurent, R., Bessière, P., Mazer, E., and Droulez, J. (2016). Design of stochastic machines dedicated to approximate bayesian inferences. IEEE Transactions on Emerging Topics in Computing (ISSN : 2168-6750).
  • [Friedman et al., 2016] Friedman, J. S., Calvet, L. E., Bessière, P., Droulez, J., and Querlioz, D. (2016). Bayesian Inference With Muller C-Elements. IEEE Transactions on Circuits and Systems, 63(6):895 – 904
  • [Grollier et al., 2016] Grollier, J., Querlioz, D., and Stiles, M. D. (2016). Spintronic nanodevices for bioinspired computing. Proceedings of the IEEE, 104(10):2024–2039.
  • [Kravchenko-Balasha et al., 2016a] Kravchenko-Balasha, N., Johnson, H., White, F. M., Heath, J. R., and Levine, R. D. (2016a). A thermodynamic-based interpretation of protein expression heterogeneity in different glioblastoma multiforme tumors identifies tumor-specific unbalanced processes. The Journal of Physical Chemistry B.
  • [Kravchenko-Balasha et al., 2016b] Kravchenko-Balasha, N., Shin, Y. S., Sutherland, A., Levine, R., and Heath, J. R. (2016b). Intercellular signaling through secreted proteins induces free-energy gradient-directed cell movement. Proceedings of the National Academy of Sciences, 113(20):5520–5525.
  • [Lobo, 2016] Lobo, J. (2016). Introduction to stochastic computing using a remote lab with reconfigurable logic. International Journal of Online Engineering (iJOE), 12(1861-2121):23–26.
  • [Mizrahi et al., 2016a] Mizrahi, A., Fukushima, A., Kubota, H., Yuasa, S., Grollier, J., and Querlioz, D. (2016a). Bio-inspired intelligent sensory processing with nanoscale stochastic magnetic tunnel junctions. arXiv preprint arXiv:1610.09394.
  • [Mizrahi et al., 2016b] Mizrahi, A., Locatelli, N., Grollier, J., and Querlioz, D. (2016b). Synchronization of electrically coupled stochastic magnetic oscillators induced by thermal and electrical noise. Physical Review B, 94(5):054419.
  • [Mizrahi et al., 2016c] Mizrahi, A., Locatelli, N., Lebrun, R., Cros, V., Fukushima, A., Kubota, H., Yuasa, S., Querlioz, D., and Grollier, J. (2016c). Controlling the phase locking of stochastic magnetic bits for ultra-low power computation. Scientific Reports, 6.
  • [Remacle et al., 2016] Remacle, F., Goldstein, A. S., and Levine, R. D. (2016). Multivariate surprisal analysis of gene expression levels. Entropy, 18(12):445.
  • [Zadran et al., 2016] Zadran, S., Remacle, F., and Levine, R. (2016). Microfluidic chip with molecular beacons detects mirnas in human csf to reliably characterize cns-specific disorders. RNA & DISEASE, 3(1).


  • [Droulez et al., 2015] Droulez, J., Colliaux, D., Houillon, A., and Bessière, P. (2015). Toward Biochemical Probabilistic Computation. ArXiv e-prints.
  • [Mizrahi et al., 2015] Mizrahi, A., Locatelli, N., Matsumoto, R., Fukushima, A., Kubota, H., Yuasa, S., Cros, V., Kim, J.-V., Grollier, J., and Querlioz, D. (2015). Magnetic stochastic oscillators: Noise-induced synchronization to underthreshold excitation and comprehensive compact model. IEEE Transactions on Magnetics, 51(11):1–4
  • [Querlioz et al., 2015] Querlioz, D., Bichler, O., Vincent, A. F., and Gamrat, C. (2015). Bioinspired program- ming of memory devices for implementing an inference engine. Proceedings of the IEEE, 103(8):1398–1416
  • [Remacle and Levine, 2015] Remacle, F. and Levine, R. (2015). Statistical thermodynamics of transcription profiles in normal development and tumorigeneses in cohorts of patients. European Biophysics Journal, 44(8):709–726.
  • [Saïghi et al., 2015] Saïghi, S., Mayr, C. G., Serrano-Gotarredona, T., Schmidt, H., Lecerf, G., Tomas, J., Grollier, J., Boyn, S., Vincent, A. F., Querlioz, D., et al. (2015). Plasticity in memristive devices for spiking neural networks. Frontiers in neuroscience, 9:51.
  • [Vincent et al., 2015a] Vincent, A. F., Larroque, J., Locatelli, N., Romdhane, N. B., Bichler, O., Gamrat, C., Zhao, W. S., Klein, J.-O., Galdin-Retailleau, S., and Querlioz, D. (2015a). Spin-transfer torque magnetic memory as a stochastic memristive synapse for neuromorphic systems. IEEE transactions on biomedical circuits and systems, 9(2):166–174.
  • [Vincent et al., 2015b] Vincent, A. F., Locatelli, N., Klein, J.-O., Zhao, W. S., Galdin-Retailleau, S., and Querlioz, D. (2015b). Analytical macrospin modeling of the stochastic switching time of spin-transfer torque devices. IEEE Transactions on Electron Devices, 62(1):164–170.
  • [Willamme et al., 2015] Willamme, R., Alsafra, Z., Arumugam, R., Eppe, G., Remacle, F., Levine, R., and Remacle, C. (2015). Metabolomic analysis of the green microalga chlamydomonas reinhardtii cultivated under day/night conditions. Journal of biotechnology, 215:20–26.


  • [Remacle F. & Levine R.D., 2014] F. Remacle and R. D. Levine (2014) Prediction of the molecular response to pertubations from single cell measurements. Med Sci (Paris), 30(12):1129–1135, Dec 2014.
  • [Plancke et al., 2014] C. Plancke, H. Vigeolas, R. Hohner, S. Roberty, B. Emonds-Alt, V. Larosa, R. Willamme, F. Duby, D. Onga Dhali, P. Thonart, S. Hiligsmann, F. Franck, G. Eppe, P. Cardol, M. Hippler, and C. Remacle. (2014) Lack of isocitrate lyase in chlamydomonas leads to changes in carbon metabolism and in the response to oxidative stress under mixotrophic growth. Plant J, 77(3):404–417, Feb 2014.
  • [Kravchenko et al., 2014] N. Kravchenko-Balasha, S. Simon, R. D. Levine, F. Remacle, and I. Exman. (2014) Computational surprisal analysis speeds-up genomic characterization of cancer processes. PLoS ONE, 9(11):e108549,2014.
  • [Zadran et al., 2014] Zadran, S., Remacle, F., and Levine, R. (2014). Surprisal analysis of glioblastoma multiform (gbm) microrna dynamics unveils tumor specific phenotype. PLoS ONE, 9(9):e108171.
  • [Zadran et al., 2014] Zadran, S., Arumugam, R., Herschman, H., Phelps, M. E., and Levine, R. D. (2014). Surprisal analysis characterizes the free energy time course of cancer cells undergoing epithelial-to- mesenchymal transition. Proc Natl Acad Sci U S A, 111(36):13235–13240.
  • [Locatelli et al., 2014] Locatelli, N., Mizrahi, A., Accioly, A., Matsumoto, R., Fukushima, A., Kubota, H., Yuasa, S., Cros, V., Pereira, L. G., Querlioz, D., Kim, J.-V., and Grollier, J. (2014). Noise-enhanced synchronization of stochastic magnetic oscillators. Phys. Rev. Applied, 2:034009.