Andrzej Mizera
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| Fakultät oder Zentrum | Fakultät für Naturwissenschaften, Technologie und Medizin | ||||
| Department | Fachbereich Informatik | ||||
| Postadresse |
Université du Luxembourg Maison du Nombre 6, Avenue de la Fonte L-4364 Esch-sur-Alzette |
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| Büroadresse | MNO, E03 0335-150 | ||||
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| Telefon | (+352) 46 66 44 5718 | ||||
2020
An efficient approach towards the source-target control of Boolean networks; ; ;
in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020), 17(6), 1932-1945
2019
Taming asynchrony for attractor detection in large Boolean networks; ; ;
in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2019), 16(1), 31-42
GPU-accelerated steady-state computation of large probabilistic Boolean networks; ;
in Formal Aspects of Computing (2019), 31(1), 27-46
A new decomposition-based method for detecting attractors in synchronous Boolean networks; ; ;
in Science of Computer Programming (2019), 180
2018
ASSA-PBN 3.0: Analysing Context-Sensitive Probabilistic Boolean Networks; ; ;
in Proceedings of the 16th International Conference on Computational Methods in Systems Biology (2018)
ASSA-PBN: A Toolbox for Probabilistic Boolean Networks; ; ;
in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2018), 15(4), 1203-1216
Reviving the two-state Markov chain approach; ;
in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2018), 15(5), 1525-1537
A Decomposition-based Approach towards the Control of Boolean Networks; ; ;
in Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (2018)
2017
A new decomposition method for attractor detection in large synchronous Boolean networks; ; ;
in Proceedings of the 3rd International Symposium on Dependable Software Engineering: Theories, Tools, and Applications (2017)
2016
Parallel Approximate Steady-state Analysis of Large Probabilistic Boolean Networks; ;
in Proceedings of the 31st ACM Symposium on Applied Computing (2016, April)
ASSA-PBN 2.0: A software tool for probabilistic Boolean networks.; ;
in Proceedings of 14th International Conference on Computational Methods in Systems Biology (2016)
Fast simulation of probabilistic Boolean networks.; ;
in Proceedings of 14th International Conference on Computational Methods in Systems Biology (2016)
Improving BDD-based attractor detection for synchronous Boolean networks.; ; ;
in SCIENCE CHINA Information Sciences (2016), 59(8), 0801011-08010116
Chemometric analysis of attenuated total reflectance infrared spectra of Proteus mirabilis strains with defined structures of LPS.; ; ; ;
in Innate Immunity (2016), 22(5), 325-335
2015
Activity tracking: A new attack on location privacy; ;
in Proceedings of the 3rd IEEE Conference on Communications and Network Security (CNS'15) (2015)
ASSA-PBN: An approximate steady-state analyser for probabilistic Boolean networks; ;
in Proceedings of the 13th International Symposium on Automated Technology for Verification and Analysis (ATVA'15) (2015)
Improving BDD-based attractor detection for synchronous Boolean networks; ; ;
in Proceedings of the 7th Asia-Pacific Symposium on Internetware (2015)
2014
Model-checking based approaches to parameter estimation of gene regulatory networks; ;
in Proceedings of 19th IEEE Conference on Engineering of Complex Computer Systems (2014)
optPBN: An Optimisation Toolbox for Probabilistic Boolean Networks; ; ; ;
in PLoS ONE (2014), 9(7), 980011-15
2013
Mathematical modelling of the Platelet-Derived Growth Factor (PDGF) signalling pathway; ; ;
in Proceedings of 4th Workshop on Computational Models for Cell Processes (CompMod'13) (2013)
A balancing act: Parameter estimation for biological models with steady-state measurements; ; ;
in Proceedings of 11th Conference on Computational Methods in Systems Biology (CMSB'13) (2013)
Recent development and biomedical applications of probabilistic Boolean networks; ; ; ; ;
in Cell Communication and Signaling (2013), 11(46),
2012
A Boolean Approach for Disentangling the Roles of Submodules to the Global Properties of a Biomodel; ;
in Fundamenta Informaticae (2012), 116(1-4), 51-63
Quantitative analysis of the self-assembly strategies of intermediate filaments from tetrameric vimentin; ; ; ; ;
in IEEE/ACM Transactions on Computational Biology and Bioinformatics (2012), 9(3), 885-898
Computational methods for quantitative submodel comparison; ;
in Katz, Evgeny (Ed.) Biomolecular Information Processing. From Logic Systems to Smart Sensors and Actuators (2012)
2011
Methods for Biochemical Model Decomposition and Quantitative Submodel Comparison; ;
in Israel Journal of Chemistry (2011), 51(1), 151164
Modelling of ultrasound therapeutic heating and numerical study of the dynamics of the induced heat shock response;
in Communications in Nonlinear Science and Numerical Simulation (2011), 16(5), 23422349
A simple mass-action model for the eukaryotic heat shock response and its mathematical validation; ; ; ; ; ; ; ;
in Natural Computing (2011), 10(1), 595-612
2010
Stochastic modelling of the eukaryotic heat shock response;
in Journal of Theoretical Biology (2010), 265(3), 455466
2009
Temperature Fields Induced by Low Power Focused Ultrasound in Soft Tissues During Gene Therapy. Numerical Predictions and Experimental Results; ; ; ;
in Archives of Acoustics (2009), 34(4), 445459
The Dynamics of Heat Shock Response Induced by Ultr asound Therapeutic Treatment;
in Awrejcewicz, J.; Kaźmierczak, M.; Mrozowski, J.; Olejnik, P. (Eds.) 10th Conference on Dynamical Systems – Theory and Applications, DSTA-2009 (2009)
Computational heuristics for simplifying a biological model; ;
in Lecture Notes in Computer Science (2009), 5635
A New Mathematical Model for the Heat Shock Response; ; ; ; ; ;
in Condon, Anne; Harel, David; Kok, Joost N.; Salomaa, Arto; Winfree, Erik (Eds.) Algorithmic Bioprocesses (2009)
2006
Applying dynamic Bayesian networks to perturbed gene expression data; ; ; ;
in BMC Bioinformatics (2006), 7
