| Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures P Wirapati, C Sotiriou, S Kunkel, P Farmer, S Pradervand, B Haibe-Kains, ... Breast Cancer Research 10, 1-11, 2008 | 1060 | 2008 |
| Extremely scalable spiking neuronal network simulation code: from laptops to exascale computers J Jordan, T Ippen, M Helias, I Kitayama, M Sato, J Igarashi, M Diesmann, ... Frontiers in neuroinformatics 12, 317068, 2018 | 153 | 2018 |
| Spiking network simulation code for petascale computers S Kunkel, M Schmidt, JM Eppler, HE Plesser, G Masumoto, J Igarashi, ... Frontiers in neuroinformatics 8, 78, 2014 | 150 | 2014 |
| Supercomputers ready for use as discovery machines for neuroscience M Helias, S Kunkel, G Masumoto, J Igarashi, JM Eppler, S Ishii, T Fukai, ... Frontiers in neuroinformatics 6, 26, 2012 | 89 | 2012 |
| A general and efficient method for incorporating precise spike times in globally time-driven simulations A Hanuschkin, S Kunkel, M Helias, A Morrison, M Diesmann Frontiers in neuroinformatics 4, 113, 2010 | 73 | 2010 |
| Meeting the memory challenges of brain-scale network simulation S Kunkel, TC Potjans, JM Eppler, HE Plesser, A Morrison, M Diesmann Frontiers in neuroinformatics 5, 35, 2012 | 68 | 2012 |
| Limits to the development of feed-forward structures in large recurrent neuronal networks S Kunkel, M Diesmann, A Morrison Frontiers in computational neuroscience 4, 160, 2011 | 56 | 2011 |
| Nest 2.12. 0 S Kunkel, R Deepu, HE Plesser, B Golosio, ME Lepperød, JM Eppler, ... Jülich Supercomputing Center, 2017 | 40 | 2017 |
| Reproducing polychronization: a guide to maximizing the reproducibility of spiking network models R Pauli, P Weidel, S Kunkel, A Morrison Frontiers in neuroinformatics 12, 46, 2018 | 37 | 2018 |
| NEST 2.18. 0 J Jordan, R Deepu, J Mitchell, JM Eppler, S Spreizer, J Hahne, ... Jülich Supercomputing Center, 2019 | 35 | 2019 |
| A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations J Hahne, M Helias, S Kunkel, J Igarashi, M Bolten, A Frommer, ... Frontiers in neuroinformatics 9, 22, 2015 | 33 | 2015 |
| NEST 2.14. 0 A Peyser, R Deepu, J Mitchell, S Appukuttan, T Schumann, JM Eppler, ... Jülich Supercomputing Center, 2017 | 25 | 2017 |
| NEST 2.16. 0 C Linssen, R Deepu, J Mitchell, ME Lepperød, J Garrido, S Spreizer, ... Jülich Supercomputing Center, 2018 | 20 | 2018 |
| The nest dry-run mode: efficient dynamic analysis of neuronal network simulation code S Kunkel, W Schenck Frontiers in neuroinformatics 11, 40, 2017 | 19 | 2017 |
| NEST 2.10. 0 H Bos, R Deepu, T Stocco, M Schmidt, JM Eppler, F Michler, HE Plesser, ... JARA-HPC, 2015 | 18 | 2015 |
| Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers J Pronold, J Jordan, BJN Wylie, I Kitayama, M Diesmann, S Kunkel Parallel computing 113, 102952, 2022 | 15 | 2022 |
| NEST 3.0 J Hahne, R Deepu, A Morales-Gregorio, J Mitchell, JM Eppler, S Spreizer, ... Computational and Systems Neuroscience, 2021 | 14 | 2021 |
| Integrating brain structure and dynamics on supercomputers SJ van Albada, S Kunkel, A Morrison, M Diesmann Brain-Inspired Computing: International Workshop, BrainComp 2013, Cetraro …, 2014 | 14 | 2014 |
| A modular workflow for performance benchmarking of neuronal network simulations J Albers, J Pronold, AC Kurth, SB Vennemo, K Haghighi Mood, A Patronis, ... Frontiers in neuroinformatics 16, 837549, 2022 | 13 | 2022 |
| NEST 3.3 S Spreizer, J Mitchell, R Gutzen, M Lober, C Linssen, G Trensch, J Jordan, ... Computational and Systems Neuroscience, 2022 | 11 | 2022 |
