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Number of items: 6.

Hegemann, B. and Unger, M. and Lee, S. S. and Stoffel-Studer, I. and van den Heuvel, J. and Pelet, S. and Koeppl, H. and Peter, M. (2015):
A Cellular System for Spatial Signal Decoding in Chemical Gradients.
35, In: Developmental Cell, (4), Elsevier, pp. 458-470, [Online-Edition: http://www.cell.com/developmental-cell/fulltext/S1534-5807%2...],

Zechner, C. and Unger, M. and Pelet, S. and Peter, M. and Koeppl, H. (2014):
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.
11, In: Nature methods, (2), pp. 197-202, [Online-Edition: http://www.nature.com/nmeth/journal/v11/n2/full/nmeth.2794.h...],

Koeppl, H. and Zechner, C. and Ganguly, A. and Pelet, S. and Peter, M. (2012):
Accounting for extrinsic variability in the estimation of stochastic rate constants.
22, In: International Journal of Robust and Nonlinear Control, (10), Wiley-Blackwell, pp. 1103-1119, [Online-Edition: http://doi.wiley.com/10.1002/rnc.2804],

Zechner, C. and Ruess, J. and Krenn, P. and Pelet, S. and Peter, M. and Lygeros, J. and Koeppl, H. (2012):
Moment-based inference predicts bimodality in transient gene expression.
109, In: Proceedings of the National Academy of Sciences of the United States of America, (21), pp. 8340-8345, [Online-Edition: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361437/?tool=pm...],

Zechner, C. and Pelet, S. and Peter, M. and Koeppl, H. (2011):
Recursive Bayesian estimation of stochastic rate constants from heterogeneous cell populations.
In: IEEE Conference on Decision and Control and European Control Conference, IEEE, pp. 5837-5843, [Online-Edition: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe...],

Koeppl, H. and Setti, G. and Pelet, S. and Mangia, M. and Petrov, T. and Peter, M. (2010):
Probability metrics to calibrate stochastic chemical kinetics.
In: Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on, [Article]

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