Profil

MIZERA Andrzej

Main Referenced Co-authors
PANG, Jun  (22)
YUAN, Qixia  (10)
Petre, Ion (8)
Qu, Hongyang (6)
Yuan, Qixia (5)
Main Referenced Keywords
Boolean networks (2); probabilistic Boolean networks (2); Aerospace Engineering (1); attractors (1); binary decision diagram (1);
Main Referenced Unit & Research Centers
Life Sciences Research Unit (1)
ULHPC - University of Luxembourg: High Performance Computing (1)
Main Referenced Disciplines
Computer science (23)
Engineering, computing & technology: Multidisciplinary, general & others (10)
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others (3)
Aerospace & aeronautics engineering (2)
Life sciences: Multidisciplinary, general & others (2)

Publications (total 40)

The most downloaded
228 downloads
Mizera, A., Pang, J., & Yuan, Q. (2018). Reviving the two-state Markov chain approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15 (5), 1525-1537. doi:10.1109/TCBB.2017.2704592 https://hdl.handle.net/10993/34366

The most cited

136 citations (Scopus®)

Norbert, D., Gambin, A., Mizera, A., Wilczyński, B., & Tiuryn, J. (2006). Applying dynamic Bayesian networks to perturbed gene expression data. BMC Bioinformatics, 7, 249. doi:10.1186/1471-2105-7-249 https://hdl.handle.net/10993/2620

HORNE, R. J., MAUW, S., MIZERA, A., Stemper, A., & THOEMEL, J. (2023). Anomaly Detection Using Deep Learning Respecting the Resources on Board a CubeSat. Journal of Aerospace Information Systems, 1-14. doi:10.2514/1.i011232
Peer reviewed

Horne, R. J., Mauw, S., Mizera, A., Stemper, A., & Thoemel, J. (2022). Autonomous Trustworthy Monitoring and Diagnosis of CubeSat Health (AtMonSat). European Space Agency.

Hasan, C., Horne, R. J., Mauw, S., & Mizera, A. (2022). Cloud removal from satellite imagery using multispectral edge-filtered conditional generative adversarial networks. International Journal of Remote Sensing, 43 (5), 1881-1893. doi:10.1080/01431161.2022.2048915
Peer Reviewed verified by ORBi

Paul, S., Su, C., Pang, J., & Mizera, A. (2020). An efficient approach towards the source-target control of Boolean networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17 (6), 1932-1945. doi:10.1109/TCBB.2019.2915081
Peer Reviewed verified by ORBi

Yuan, Q., Mizera, A., Pang, J., & Qu, H. (2019). A new decomposition-based method for detecting attractors in synchronous Boolean networks. Science of Computer Programming, 180, 18-35. doi:10.1016/j.scico.2019.05.001
Peer Reviewed verified by ORBi

Mizera, A., Pang, J., & Yuan, Q. (2019). GPU-accelerated steady-state computation of large probabilistic Boolean networks. Formal Aspects of Computing, 31 (1), 27-46. doi:10.1007/s00165-018-0470-6
Peer Reviewed verified by ORBi

Mizera, A., Pang, J., Qu, H., & Yuan, Q. (2019). Taming asynchrony for attractor detection in large Boolean networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16 (1), 31-42. doi:10.1109/TCBB.2018.2850901
Peer reviewed

Mizera, A., Pang, J., Su, C., & Yuan, Q. (2018). ASSA-PBN: A Toolbox for Probabilistic Boolean Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15 (4), 1203-1216. doi:10.1109/TCBB.2017.2773477
Peer reviewed

Paul, S., Su, C., Pang, J., & Mizera, A. (2018). 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. ACM. doi:10.1145/3233547.3233550
Peer reviewed

Mizera, A., Pang, J., Qu, H., & Yuan, Q. (2018). ASSA-PBN 3.0: Analysing Context-Sensitive Probabilistic Boolean Networks. In Proceedings of the 16th International Conference on Computational Methods in Systems Biology (pp. 277-284). Springer Science & Business Media B.V. doi:10.1007/978-3-319-99429-1_16
Peer reviewed

Mizera, A., Pang, J., & Yuan, Q. (2018). Reviving the two-state Markov chain approach. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15 (5), 1525-1537. doi:10.1109/TCBB.2017.2704592
Peer Reviewed verified by ORBi

Mizera, A., Pang, J., Qu, H., & Yuan, Q. (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 (pp. 232-249). Springer Science & Business Media B.V.
Peer reviewed

Mizera, A., Pang, J., & Yuan, Q. (2016). Parallel Approximate Steady-state Analysis of Large Probabilistic Boolean Networks. In Proceedings of the 31st ACM Symposium on Applied Computing. ACM.
Peer reviewed

Zarnowiec, P., Mizera, A., Chrapek, M., Urbaniak, M., & Kaca, W. (2016). Chemometric analysis of attenuated total reflectance infrared spectra of Proteus mirabilis strains with defined structures of LPS. Innate Immunity, 22 (5), 325-335. doi:10.1177/1753425916647470
Peer Reviewed verified by ORBi

Mizera, A., Pang, J., & Yuan, Q. (2016). Fast simulation of probabilistic Boolean networks. In Proceedings of 14th International Conference on Computational Methods in Systems Biology (pp. 216-231). Berlin, Germany: Springer.
Peer reviewed

Mizera, A., Pang, J., & Yuan, Q. (2016). ASSA-PBN 2.0: A software tool for probabilistic Boolean networks. In Proceedings of 14th International Conference on Computational Methods in Systems Biology (pp. 309-315). Berlin, Germany: Springer.
Peer reviewed

Mizera, A., Pang, J., & Yuan, Q. (2016). GPU-accelerated steady-state analysis of probabilistic Boolean networks [Poster presentation]. 14th International Conference on Computational Methods in Systems Biology.

Yuan, Q., Qu, H., Pang, J., & Mizera, A. (2016). Improving BDD-based attractor detection for synchronous Boolean networks. Science China Information Sciences, 59 (8), 080101:1-080101:16. doi:10.1007/s11432-016-5594-9
Peer reviewed

Mizera, A., Pang, J., & Yuan, Q. (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) (pp. 214-220). Springer.
Peer reviewed

Qu, H., Yuan, Q., Pang, J., & Mizera, A. (2015). Improving BDD-based attractor detection for synchronous Boolean networks. In Proceedings of the 7th Asia-Pacific Symposium on Internetware. ACM.
Peer reviewed

Chen, X., Mizera, A., & Pang, J. (2015). Activity tracking: A new attack on location privacy. In Proceedings of the 3rd IEEE Conference on Communications and Network Security (CNS'15) (pp. 22-30). IEEE CS.
Peer reviewed

Trairatphisan, P., Mizera, A., Pang, J., Tantar, A.-A., & Sauter, T. (01 July 2014). optPBN: An Optimisation Toolbox for Probabilistic Boolean Networks. PLoS ONE, 9 (7), 98001 (1-15. doi:10.1371/journal.pone.0098001
Peer Reviewed verified by ORBi

Mizera, A., Pang, J., & Yuan, Q. (2014). Model-checking based approaches to parameter estimation of gene regulatory networks. In Proceedings of 19th IEEE Conference on Engineering of Complex Computer Systems (pp. 206-209). IEEE CS. doi:10.1109/ICECCS.2014.38
Peer reviewed

Trairatphisan, P., Mizera, A., Pang, J., Tantar, A.-A., Schneider, J., & Sauter, T. (01 July 2013). Recent development and biomedical applications of probabilistic Boolean networks. Cell Communication and Signaling, 11 (46). doi:10.1186/1478-811X-11-46
Peer Reviewed verified by ORBi

Mizera, A., Pang, J., Sauter, T., & Trairatphisan, P. (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) (pp. 35).

Mizera, A., Pang, J., Sauter, T., & Trairatphisan, P. (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) (pp. 253-254). Springer.
Peer reviewed

Czeizler, E., Mizera, A., & Petre, I. (2012). A Boolean Approach for Disentangling the Roles of Submodules to the Global Properties of a Biomodel. Fundamenta Informaticae, 116 (1-4), 51-63. doi:10.3233/FI-2012-668
Peer Reviewed verified by ORBi

Mizera, A., Czeizler, E., & Petre, I. (2012). Self-assembly models of variable resolution. Lecture Notes in Computer Science, 7625, 181 - 203. doi:10.1007/978-3-642-35524-0_8
Peer reviewed

Czeizler, E., Mizera, A., Czeizler, E., Back, R.-J., Eriksson, J. E., & Petre, I. (2012). Quantitative analysis of the self-assembly strategies of intermediate filaments from tetrameric vimentin. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9 (3), 885 - 898. doi:10.1109/TCBB.2011.154
Peer Reviewed verified by ORBi

Mizera, A., Czeizler, E., & Petre, I. (2012). Computational methods for quantitative submodel comparison. In E. Katz (Ed.), Biomolecular Information Processing. From Logic Systems to Smart Sensors and Actuators (pp. 323 - 346). Weinheim, Germany: Wiley-VCH Verlag GmbH. doi:10.1002/9783527645480.ch17
Peer reviewed

Mizera, A. (2011). Methods for construction and analysis of computational models in systems biology: applications to the modelling of the heat shock response and the self-assembly of intermediate filaments [Doctoral thesis, Åbo Akademi University]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/22944

Mizera, A., Czeizler, E., & Petre, I. (2011). Methods for Biochemical Model Decomposition and Quantitative Submodel Comparison. Israel Journal of Chemistry, 51 (1), 151–164. doi:10.1002/ijch.201000067
Peer Reviewed verified by ORBi

Petre, I., Mizera, A., Hyder, C. L., Meinander, A., Mikhailov, A., Morimoto, R. I., Sistonen, L., Eriksson, J. E., & Back, R.-J. (2011). A simple mass-action model for the eukaryotic heat shock response and its mathematical validation. Natural Computing, 10 (1), 595-612. doi:10.1007/s11047-010-9216-y
Peer Reviewed verified by ORBi

Mizera, A., & Gambin, B. (2011). Modelling of ultrasound therapeutic heating and numerical study of the dynamics of the induced heat shock response. Communications in Nonlinear Science and Numerical Simulation, 16 (5), 2342–2349. doi:10.1016/j.cnsns.2010.04.056
Peer Reviewed verified by ORBi

Mizera, A., & Gambin, B. (2010). Stochastic modelling of the eukaryotic heat shock response. Journal of Theoretical Biology, 265 (3), 455–466. doi:10.1016/j.jtbi.2010.04.029
Peer Reviewed verified by ORBi

Petre, I., Mizera, A., & Back, R.-J. (2009). Computational heuristics for simplifying a biological model. Lecture Notes in Computer Science, 5635, 399-408. doi:10.1007/978-3-642-03073-4_41
Peer reviewed

Petre, I., Mizera, A., Hyder, C. L., Mikhailov, A., Eriksson, J. E., Sistonen, L., & Back, R.-J. (2009). A New Mathematical Model for the Heat Shock Response. In A. Condon, D. Harel, J. N. Kok, A. Salomaa, ... E. Winfree (Eds.), Algorithmic Bioprocesses (pp. 411-425). Berlin Heidelberg, Unknown/unspecified: Springer-Verlag.
Peer reviewed

Gambin, B., Kujawska, T., Kruglenko, E., Mizera, A., & Nowicki, A. (2009). Temperature Fields Induced by Low Power Focused Ultrasound in Soft Tissues During Gene Therapy. Numerical Predictions and Experimental Results. Archives of Acoustics, 34 (4), 445–459.
Peer reviewed

Mizera, A., & Gambin, B. (2009). The Dynamics of Heat Shock Response Induced by Ultr asound Therapeutic Treatment. In J. Awrejcewicz, M. Kaźmierczak, J. Mrozowski, ... P. Olejnik (Eds.), 10th Conference on Dynamical Systems – Theory and Applications, DSTA-2009 (pp. 847-852). Łódź, Poland: Left Grupa.
Peer reviewed

Norbert, D., Gambin, A., Mizera, A., Wilczyński, B., & Tiuryn, J. (2006). Applying dynamic Bayesian networks to perturbed gene expression data. BMC Bioinformatics, 7, 249. doi:10.1186/1471-2105-7-249
Peer Reviewed verified by ORBi

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