Browse ORBilu by Open Access
- What it is and what it isn't
- Green Road / Gold Road?
- Ready to Publish. Now What?
- How can I support the OA movement?
- Where can I learn more?
ORBilu is a project developed by
Showing results 61 to 80 of 179
   ASSA-PBN: A Toolbox for Probabilistic Boolean NetworksMizera, Andrzej  ; Pang, Jun ; et alin IEEE/ACM Transactions on Computational Biology and Bioinformatics (2018), 15(4), 1203-1216 Detailed reference viewed: 99 (4 UL) ASSA-PBN 3.0: Analysing Context-Sensitive Probabilistic Boolean NetworksMizera, Andrzej ; Pang, Jun ; et alin Proceedings of the 16th International Conference on Computational Methods in Systems Biology (2018) Detailed reference viewed: 133 (3 UL)A Decomposition-based Approach towards the Control of Boolean NetworksPaul, Soumya ; ; Pang, Jun et alin Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (2018) Detailed reference viewed: 135 (4 UL)L-CMP: an automatic learning-based parameterized verification tool; ; Pang, Jun in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (2018) Detailed reference viewed: 111 (1 UL)On the Full Control of Boolean NetworksPaul, Soumya ; Pang, Jun ; in Proceedings of the 16th International Conference on Computational Methods in Systems Biology (2018) Detailed reference viewed: 117 (4 UL)Tagvisor: A privacy advisor for sharing hashtags; ; et al in Proceedings of The Web Conference 2018 (WWW'18) (2018) Detailed reference viewed: 61 (2 UL)Learning probabilistic models for model checking: an evolutionary approach and an empirical study; ; et al in International Journal on Software Tools for Technology Transfer (2018), 20(6), 689-704 Detailed reference viewed: 119 (4 UL)An Automatic Proving Approach to Parameterized Verification; ; et al in ACM Transactions on Computational Logic (2018), 19(4), 1-27 Detailed reference viewed: 146 (1 UL)Towards the Existential Control of Boolean Networks: A Preliminary ReportPaul, Soumya ; Pang, Jun ; in Proceedings of the 4th International Symposium on Dependable Software Engineering. Theories, Tools, and Applications (2018) Detailed reference viewed: 92 (1 UL)Reviving the two-state Markov chain approachMizera, Andrzej ; Pang, Jun ; Yuan, Qixia in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2018), 15(5), 1525-1537 Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in the study of such ... [more ▼] Probabilistic Boolean networks (PBNs) is a well-established computational framework for modelling biological systems. The steady-state dynamics of PBNs is of crucial importance in the study of such systems. However, for large PBNs, which often arise in systems biology, obtaining the steady-state distribution poses a significant challenge. In this paper, we revive the two-state Markov chain approach to solve this problem. This paper contributes in three aspects. First, we identify a problem of generating biased results with the approach and we propose a few heuristics to avoid such a pitfall. Secondly, we conduct an extensive experimental comparison of the extended two-state Markov chain approach and another approach based on the Skart method. We analyse the results with machine learning techniques and we show that statistically the two-state Markov chain approach has a better performance. Finally, we demonstrate the potential of the extended two-state Markov chain approach on a case study of a large PBN model of apoptosis in hepatocytes. [less ▲] Detailed reference viewed: 163 (7 UL)Proceedings of the 12th International Symposium on Theoretical Aspects of Software EngineeringPang, Jun ; ; et alBook published by IEEE Computer Society (2018) Detailed reference viewed: 55 (2 UL)A new decomposition method for attractor detection in large synchronous Boolean networksMizera, Andrzej ; Pang, Jun ; et alin Proceedings of the 3rd International Symposium on Dependable Software Engineering: Theories, Tools, and Applications (2017) Detailed reference viewed: 164 (5 UL)DeepCity: A Feature Learning Framework for Mining Location Check-InsPang, Jun ; in Proceedings of the 11th International Conference on Web and Social Media (ICWSM'17) (2017) Detailed reference viewed: 123 (6 UL)Quantifying location socialityPang, Jun ; in Proc. 28th ACM Conference on Hypertext and Social Media - HT'17 (2017) Detailed reference viewed: 129 (1 UL)Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study; ; Yuan, Qixia et alin Proceedings of 20th International Conference on Fundamental Approaches to Software Engineering (2017) Detailed reference viewed: 146 (11 UL)Does #like4like indeed provoke more likes?; ; et al in Proceedings of the 16th IEEE/WIC/ACM International Conference on Web Intelligence (WI'17) (2017) Detailed reference viewed: 129 (1 UL)Formal modelling and analysis of receipt-free auction protocols in applied pi; ; Pang, Jun in Computers and Security (2017), 65 Detailed reference viewed: 181 (2 UL)walk2friends: Inferring Social Links from Mobility Profiles; ; Pang, Jun et alin Proceedings of the 24th ACM International Conference on Computer and Communications Security (2017) Detailed reference viewed: 111 (5 UL)A verification framework for stateful security protocols; ; Pang, Jun et alin Proceedings of the 19th International Conference on Formal Engineering Methods (2017) Detailed reference viewed: 147 (1 UL)Semantic annotation for places in LBSN through graph embedding; ; Pang, Jun et alin Proceedings of the 26th ACM International Conference on Information and Knowledge Management - CIKM'17 (2017) Detailed reference viewed: 130 (1 UL) |
||
