Heinz Koeppl

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Christoph ZechnerMax Planck Institute of Molecular Cell Biology and GeneticsVerified email at mpi-cbg.de
Wasiur R. KhudaBukhshSchool of Mathematical Sciences, The University of NottinghamVerified email at nottingham.ac.uk
Tatjana PetrovUniversity of KonstanzVerified email at uni-konstanz.de
Marc HafnerGenentechVerified email at gene.com
Michael UngerETH ZurichVerified email at control.ee.ethz.ch
Arnab GangulyLSUVerified email at lsu.edu
Bastian AltResearch Associate, Technische Universität DarmstadtVerified email at tu-darmstadt.de
Amr RizkProfessor of Computer Science (Networks and Communication Systems), University of Duisburg-EssenVerified email at uni-due.de
Tim PrangemeierElectrical and Mechanical Engineering, Technische Universität DarmstadtVerified email at bcs.tu-darmstadt.de
Abdelhak M. ZoubirProfessor of Signal Processing, Technische Universität DarmstadtVerified email at spg.tu-darmstadt.de
Adrian ŠošićSenior Data Scientist, Merck KGaAVerified email at merckgroup.com
Jérôme FeretChargé de recherche, Inria ParisVerified email at inria.fr
Loïc PaulevéCNRS/LaBRI, Bordeaux, FranceVerified email at ens-cachan.org
Preetam NandyGoogleVerified email at google.com
Pablo MeyerResearch Staff Member, IBMVerified email at us.ibm.com
James LuGenentechVerified email at gene.com
Andreas WagnerUniversity of ZurichVerified email at ieu.uzh.ch
Elias AugustReykjavik UniversityVerified email at ru.is
Derya AltıntanHacettepe ÜniversitesiVerified email at hacettepe.edu.tr
Jakob RuessInria Paris & Institut PasteurVerified email at inria.fr

Heinz Koeppl

Technische Universität Darmstadt, Dept. Electrical Engineering and Dept. Biology

Verified email at bcs.tu-darmstadt.de - Homepage

synthetic biology machine learning multi-agent systems self-organization collective intelligence


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Moment-based inference predicts bimodality in transient gene expression C Zechner, J Ruess, P Krenn, S Pelet, M Peter, J Lygeros, H Koeppl Proceedings of the National Academy of Sciences 109 (21), 8340-8345, 2012	245	2012
Inferring causal molecular networks: empirical assessment through a community-based effort SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ... Nature Methods 13 (4), 310-318, 2016	217	2016
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings C Zechner, M Unger, S Pelet, M Peter, H Koeppl Nature Methods 11 (2), 197-202, 2014	141	2014
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge AL Tarca, M Lauria, M Unger, E Bilal, S Boue, K Kumar Dey, J Hoeng, ... Bioinformatics 29 (22), 2892-2899, 2013	126	2013
Verification of systems biology research in the age of collaborative competition P Meyer, LG Alexopoulos, T Bonk, A Califano, CR Cho, A De La Fuente, ... Nature biotechnology 29 (9), 811-815, 2011	95	2011
‘Glocal’robustness analysis and model discrimination for circadian oscillators M Hafner, H Koeppl, M Hasler, A Wagner PLoS computational biology 5 (10), e1000534, 2009	95	2009
Effect of network architecture on synchronization and entrainment properties of the circadian oscillations in the suprachiasmatic nucleus M Hafner, H Koeppl, D Gonze PLoS computational biology 8 (3), e1002419, 2012	75	2012
Digitally enhanced analog circuits: System aspects B Murmann, C Vogel, H Koeppl 2008 IEEE International Symposium on Circuits and Systems, 560-563, 2008	65	2008
Inverse reinforcement learning in swarm systems A Šošić, WR KhudaBukhsh, AM Zoubir, H Koeppl arXiv preprint arXiv:1602.05450, 2016	61	2016
Spatial simulations in systems biology: from molecules to cells M Klann, H Koeppl International journal of molecular sciences 13 (6), 7798-7827, 2012	60	2012
Lumpability abstractions of rule-based systems J Feret, T Henzinger, H Koeppl, T Petrov Theoretical Computer Science 431, 137-164, 2012	60	2012
Design and analysis of biomolecular circuits: engineering approaches to systems and synthetic biology H Koeppl, D Densmore, G Setti, M di Bernardo Springer Science & Business Media, 2011	60	2011
Attention-based transformers for instance segmentation of cells in microstructures T Prangemeier, C Reich, H Koeppl 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020	54	2020
A cellular system for spatial signal decoding in chemical gradients B Hegemann, M Unger, SS Lee, I Stoffel-Studer, J van den Heuvel, ... Developmental cell 35 (4), 458-470, 2015	53	2015
Spatial modeling of vesicle transport and the cytoskeleton: the challenge of hitting the right road M Klann, H Koeppl, M Reuss PLoS One 7 (1), e29645, 2012	51	2012
Jump-diffusion approximation of stochastic reaction dynamics: error bounds and algorithms A Ganguly, D Altintan, H Koeppl Multiscale Modeling & Simulation 13 (4), 1390-1419, 2015	49	2015
Hybrid spatial Gillespie and particle tracking simulation M Klann, A Ganguly, H Koeppl Bioinformatics 28 (18), i549-i555, 2012	46	2012
Uncoupled analysis of stochastic reaction networks in fluctuating environments C Zechner, H Koeppl PLoS computational biology 10 (12), e1003942, 2014	43	2014
An adaptive cellular nonlinear network and its application H Koeppl, LO Chua IEICE Proceedings Series 41 (17PM1-B-1), 2007	43	2007
An efficient scheme for nonlinear modeling and predistortion in mixed-signal systems H Koeppl, P Singerl IEEE Transactions on Circuits and Systems II: Express Briefs 53 (12), 1368-1372, 2006	42	2006

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