Qixia Yuan
Título
Citado por
Citado por
Año
ASSA-PBN: an approximate steady-state analyser of probabilistic Boolean networks
A Mizera, J Pang, Q Yuan
International Symposium on Automated Technology for Verification and …, 2015
192015
Taming asynchrony for attractor detection in large Boolean networks
A Mizera, J Pang, H Qu, Q Yuan
IEEE/ACM transactions on computational biology and bioinformatics 16 (1), 31-42, 2018
132018
Improving BDD-based attractor detection for synchronous Boolean networks
Q Yuan, H Qu, J Pang, A Mizera
Science China Information Sciences 59 (8), 080101, 2016
132016
ASSA-PBN 2.0: A Software Tool for Probabilistic Boolean Networks
A Mizera, J Pang, Q Yuan
International Conference on Computational Methods in Systems Biology, 309-315, 2016
122016
ASSA-PBN: a toolbox for probabilistic Boolean networks
A Mizera, J Pang, C Su, Q Yuan
IEEE/ACM transactions on computational biology and bioinformatics 15 (4 …, 2017
102017
Reviving the two-state Markov chain approach
A Mizera, J Pang, Q Yuan
IEEE/ACM transactions on computational biology and bioinformatics 15 (5 …, 2017
82017
Reviving the two-state markov chain approach (technical report)
A Mizera, J Pang, Q Yuan
arXiv preprint arXiv:1501.01779, 2015
82015
Should we learn probabilistic models for model checking? A new approach and an empirical study
J Wang, J Sun, Q Yuan, J Pang
International Conference on Fundamental Approaches to Software Engineering, 3-21, 2017
72017
A new decomposition method for attractor detection in large synchronous Boolean networks
A Mizera, J Pang, H Qu, Q Yuan
International Symposium on Dependable Software Engineering: Theories, Tools …, 2017
62017
Fast simulation of probabilistic Boolean networks
A Mizera, J Pang, Q Yuan
International Conference on Computational Methods in Systems Biology, 216-231, 2016
62016
Parallel approximate steady-state analysis of large probabilistic Boolean networks
A Mizera, J Pang, Q Yuan
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 1-8, 2016
62016
Reviving the two-state Markov chain approach (Technical report)(2015)
A Mizera, J Pang, Q Yuan
Accessed on http://arxiv. org/abs/1501.01779, 0
6
Learning probabilistic models for model checking: an evolutionary approach and an empirical study
J Wang, J Sun, Q Yuan, J Pang
International Journal on Software Tools for Technology Transfer 20 (6), 689-704, 2018
42018
Probabilistic model checking of the PDGF signaling pathway
Q Yuan, P Trairatphisan, J Pang, S Mauw, M Wiesinger, T Sauter
Transactions on Computational Systems Biology XIV, 151-180, 2012
42012
GPU-accelerated steady-state computation of large probabilistic Boolean networks
A Mizera, J Pang, Q Yuan
Formal Aspects of Computing 31 (1), 27-46, 2019
32019
Taming asynchrony for attractor detection in large Boolean networks (technical report)
A Mizera, J Pang, H Qu, Q Yuan
arXiv preprint arXiv:1704.06530, 2017
32017
A study of the PDGF signaling pathway with PRISM
Q Yuan, J Pang, S Mauw, P Trairatphisan, M Wiesinger, T Sauter
arXiv preprint arXiv:1109.1367, 2011
32011
ASSA-PBN 3.0: Analysing Context-Sensitive Probabilistic Boolean Networks
A Mizera, J Pang, H Qu, Q Yuan
International Conference on Computational Methods in Systems Biology, 277-284, 2018
22018
Model-checking based approaches to parameter estimation of gene regulatory networks
A Mizera, J Pang, Q Yuan
2014 19th International Conference on Engineering of Complex Computer …, 2014
22014
Weak leakage resilient extractable hash proof system and construction for weak leakage resilient CCA-secure public-key encryption
C Hu, Z Yu, R Yang, Q Xu, Y Zhou, Q Yuan
International Journal of Embedded Systems 7 (3-4), 216-229, 2015
12015
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