| 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 | 249 | 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 | 156 | 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 | 133 | 2013 |
| 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 | 61 | 2015 |
| Reconstructing dynamic molecular states from single-cell time series L Huang, L Pauleve, C Zechner, M Unger, AS Hansen, H Koeppl Journal of The Royal Society Interface 13 (122), 20160533, 2016 | 21 | 2016 |
| Optimal variational perturbations for the inference of stochastic reaction dynamics C Zechner, P Nandy, M Unger, H Koeppl 2012 IEEE 51st IEEE conference on decision and control (CDC), 5336-5341, 2012 | 11 | 2012 |
| Consortium HPN-DREAM SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ... Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y …, 2016 | 10 | 2016 |
| Pulse width modulation of liquid flows: Towards dynamic control of cell microenvironments M Unger, SS Lee, M Peter, H Koeppl 15th International Conference on miniaturized systems for chemistry and life …, 2011 | 8 | 2011 |
| Optimal perturbations for the identification of stochastic reaction dynamics P Nandy, M Unger, C Zechner, H Koeppl IFAC Proceedings Volumes 45 (16), 686-691, 2012 | 7 | 2012 |
| GB Mills, JW Gray, M SM Hill, LM Heiser, T Cokelaer, M Unger, NK Nesser, DE Carlin, Y Zhang, ... Kellen, T. Norman, S. Friend, AA Qutub, Y. Fertig, EJ Guan, M. Song, JM …, 2016 | 6 | 2016 |
| Learning diagnostic signatures from microarray data using L1-regularized logistic regression P Nandy, M Unger, C Zechner, KK Dey, H Koeppl Systems Biomedicine 1 (4), 240-246, 2013 | 5 | 2013 |
| From microscopy data to in silico environments for in vivo-oriented simulations N Hiroi, M Klann, K Iba, P Heras Ciechomski, S Yamashita, A Tabira, ... EURASIP Journal on Bioinformatics and Systems Biology 2012, 1-11, 2012 | 5 | 2012 |
| IMPROVER DSC Collaborators. 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, J Hoeng, H Koeppl, ... Bioinformatics 29 (22), 2892-9, 2013 | 3 | 2013 |
| Interrogating the single cell: computational and experimental methods for optimal live cell experiments MP Unger ETH Zurich, 2014 | 2 | 2014 |
| Pooling single-cell recordings: Scalable inference through heterogeneous kinetics C Zechner, M Unger, S Pelet, M Peter, H Koeppl arXiv preprint arXiv:1302.3152, 2013 | 2 | 2013 |
| A CELLULAR SYSTEM FOR SPATIAL SIGNAL DECODING B Hegemann, M Unger, SS Lee, I Stoffel-Studer DISS. ETH NO. 22356, 137, 2014 | | 2014 |
| Supporting Information for Reconstructing dynamic molecular states from single-cell time series L Huang, L Pauleve, C Zechner, M Unger, AS Hansen, H Koeppl | | |
| Talk abstracts SM Hill, LM Heiser, T Cokelaer, M Unger, H Koeppl, G Stolovitzky, ... | | |
Heinz KoepplTechnische Universität Darmstadt, Dept. Electrical Engineering and Dept. Biology在 bcs.tu-darmstadt.de 的电子邮件经过验证
