Thematische Bibliographien / Control Boolean network

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Auswahl der wissenschaftlichen Literatur zum Thema „Control Boolean network“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

Zuletzt aktualisiert am 31. Juli 2025

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Zeitschriftenartikel zum Thema "Control Boolean network"

CHEN, HONGWEI, YANG LIU, and JIANQUAN LU. "SYNCHRONIZATION CRITERIA FOR TWO BOOLEAN NETWORKS BASED ON LOGICAL CONTROL." International Journal of Bifurcation and Chaos 23, no. 11 (2013): 1350178. http://dx.doi.org/10.1142/s0218127413501782.

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This paper investigates the complete synchronization of two Boolean networks via logic control. Both feedback control and open-loop control are proposed to make the slave network completely synchronized with the master Boolean network. Using the algebraic state-space representation of Boolean networks, we derive several necessary and sufficient conditions for complete synchronization between two Boolean networks. Two examples are given to illustrate the obtained results.

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Li, Zhiqiang, Jinli Song, and Huimin Xiao. "Reachability and Controllability Analysis of Periodic Switched Boolean Control Networks." Journal of Robotics and Mechatronics 26, no. 5 (2014): 573–79. http://dx.doi.org/10.20965/jrm.2014.p0573.

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The reachability and controllability of switched Boolean (control) network are discussed in this paper. Based on semi-tensor product, using the vector form of Boolean logical variable, the switched Boolean (control) network is expressed as a discrete time system with state and control variables. For the switched Boolean network without control, the stabilization by suitable switching signal is discussed. Also, the controllability of the periodic switching signal is learned, and the conditions for stability and controllability of periodic switched Boolean networks avoiding states setCare obtain

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Gao, Bo, Haipeng Peng, Dawei Zhao, Wenguang Zhang, and Yixian Yang. "Attractor Transformation by Impulsive Control in Boolean Control Network." Mathematical Problems in Engineering 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/674571.

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Boolean control networks have recently been attracting considerable interests as computational models for genetic regulatory networks. In this paper, we present an approach of impulsive control for attractor transitions in Boolean control networks based on the recent developed matrix semitensor product theory. The reachability of attractors is estimated, and the controller is also obtained. The general derivation proposed here is exemplified with a kind of gene model, which is the protein-nucleic acid interactions network, on numerical simulations.

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Shi, Wenping, Bo Wu, and Jing Han. "A Note on the Observability of Temporal Boolean Control Network." Abstract and Applied Analysis 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/631639.

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Temporal Boolean network is a generalization of the Boolean network model that takes into account the time series nature of the data and tries to incorporate into the model the possible existence of delayed regulatory interactions among genes. This paper investigates the observability problem of temporal Boolean control networks. Using the semi tensor product of matrices, the temporal Boolean networks can be converted into discrete time linear dynamic systems with time delays. Then, necessary and sufficient conditions on the observability via two kinds of inputs are obtained. An example is giv

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Zhao, Yin, Bijoy K. Ghosh, and Daizhan Cheng. "Control of Large-Scale Boolean Networks via Network Aggregation." IEEE Transactions on Neural Networks and Learning Systems 27, no. 7 (2016): 1527–36. http://dx.doi.org/10.1109/tnnls.2015.2442593.

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Wang, Cailu, and Yuegang Tao. "Conversion between Logic and Algebraic Expressions of Boolean Control Networks." Applied Sciences 10, no. 20 (2020): 7180. http://dx.doi.org/10.3390/app10207180.

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The conversion between logic and algebraic expressions of Boolean control networks plays a worthy role in the analysis and design of digital circuits. In this paper, for a single Boolean function, a direct conversion between the minterm canonical form and the structure matrix is provided. For a Boolean control network consisting of systems of Boolean functions, two algorithms are developed to achieve the mutual conversion between the logic and algebraic expressions. The presented algorithms decrease exponentially the complexity of the semi-tensor product based method. Some numerical examples a

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Wei, Qiang, Cheng-jun Xie, Xu-ri Kou, and Wei Shen. "Delay Partial Synchronization of Mutual Delay Coupled Boolean Networks." Measurement and Control 53, no. 5-6 (2020): 870–75. http://dx.doi.org/10.1177/0020294019882967.

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This paper studies the delay partial synchronization for mutual delay-coupled Boolean networks. First, the mutual delay-coupled Boolean network model is presented. Second, some necessary and sufficient conditions are derived to ensure the delay partial synchronization of the mutual delay-coupled Boolean networks. The upper bound of synchronization time is obtained. Finally, an example is provided to illustrate the efficiency of the theoretical analysis.

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Li, Fangfei, Xiwen Lu, and Zhaoxu Yu. "Optimal control algorithms for switched Boolean network." Journal of the Franklin Institute 351, no. 6 (2014): 3490–501. http://dx.doi.org/10.1016/j.jfranklin.2014.03.008.

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Sun, Xiaolei, Naiming Qi, and Weiran Yao. "Boolean Networks-Based Auction Algorithm for Task Assignment of Multiple UAVs." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/425356.

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This paper presents an application of Boolean networks-based auction algorithm (BNAA) for task assignment in unmanned aerial vehicles (UAVs) systems. Under reasonable assumptions, the assignment framework consists of mission control system, communication network, and ground control station. As the improved algorithm of consensus-based bundle algorithm (CBBA), the BNAA utilizes a cluster-based combinatorial auction policy to handle multiple tasks. Instead of empirical method based on look-up table about conditional variables, Boolean network is introduced into consensus routine of BNAA for solv

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Chen, Cheng, and Wei Zhu. "Synchronization Analysis of Boolean Network." Applied Mechanics and Materials 432 (September 2013): 528–32. http://dx.doi.org/10.4028/www.scientific.net/amm.432.528.

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Boolean network and its synchronization have been gradually used to the global behavior analysis of large gene regulatory network. Network synchronization depends mainly on the dynamics of each node and the topology of the network. In this paper, using the semi-tensor product of matrices, a necessary and sufficient condition based on transition matrix for Boolean network complete synchronization is presented. The synchronization of Boolean control network is also discussed. Two examples are given to illustrate the theoretical result.

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Dissertationen zum Thema "Control Boolean network"

Magnini, Matteo. "An information theory analysis of critical Boolean networks as control software for robots." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23062/.

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This work is an analysis of critical random Boolean networks used as control software for robots. The main goal is to find if there are relations between information theory measures on robot's sensors and actuators and the capability of the robot to achieve a particular task. Secondary goals are to verify if just the number of nodes of the networks is significant to obtain better populations of controllers for a given task and if a Boolean network can perform well in more than one single task. Results show that for certain tasks there is a strongly positively correlation between some informati

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Münzner, Ulrike Tatjana Elisabeth. "From birth to birth A cell cycle control network of S. cerevisiae." Doctoral thesis, Humboldt-Universität zu Berlin, 2017. http://dx.doi.org/10.18452/18566.

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Der Zellzyklus organisiert die Zellteilung, und kontrolliert die Replikation der DNA sowie die Weitergabe des Genoms an die nächste Zellgeneration. Er unterliegt einer strengen Kontrolle auf molekularer Ebene. Diese molekularen Kontrollmechanismen sind für das Überleben eines Organismus essentiell, da Fehler Krankheiten begüngstigen können. Vor allem Krebs ist assoziiert mit Abweichungen im Ablauf des Zellzyklus. Die Aufklärung solcher Kontrollmechanismen auf molekularer Ebene ermöglicht einerseits das Verständnis deren grundlegender Funktionsweise, andererseits können solche Erkenntnisse

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Goudarzi, Alireza. "On the Effect of Topology on Learning and Generalization in Random Automata Networks." PDXScholar, 2011. https://pdxscholar.library.pdx.edu/open_access_etds/193.

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We extend the study of learning and generalization in feed forward Boolean networks to random Boolean networks (RBNs). We explore the relationship between the learning capability and the network topology, the system size, the training sample size, and the complexity of the computational tasks. We show experimentally that there exists a critical connectivity Kc that improves the generalization and adaptation in networks. In addition, we show that in finite size networks, the critical K is a power-law function of the system size N and the fraction of inputs used during the training. We explain w

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Pardo, Jérémie. "Méthodes d'inférence de cibles thérapeutiques et de séquences de traitement." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG011.

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Un enjeu majeur de la médecine des réseaux est l’identification des perturbations moléculaires induites par les maladies complexes et les thérapies afin de réaliser une reprogrammation cellulaire. L’action de la reprogrammation est le résultat de l’application d’un contrôle. Dans cette thèse, nous étendons le contrôle unique des réseaux biologiques en étudiant le contrôle séquentiel des réseaux booléens. Nous présentons un nouveau cadre théorique pour l’étude formelle des séquences de contrôle. Nous considérons le contrôle par gel de noeuds. Ainsi, une variable du réseau booléen peut être fixé

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Jiao, Yue, and 焦月. "Mathematical models for control of probabilistic Boolean networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41508634.

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Chen, Xi, and 陈曦. "On construction and control of probabilistic Boolean networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48329605.

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Modeling gene regulation is an important problem in genomic research. The Boolean network (BN) and its generalization Probabilistic Boolean network (PBN) have been proposed to model genetic regulatory interactions. BN is a deterministic model while PBN is a stochastic model. In a PBN, on one hand, its stationary distribution gives important information about the long-run behavior of the network. On the other hand, one may be interested in system synthesis which requires the construction of networks from the observed stationary distribution. This results in an inverse problem of constructin

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Jiao, Yue. "Mathematical models for control of probabilistic Boolean networks." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41508634.

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Choudhary, Ashish. "Intervention in gene regulatory networks." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4284.

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In recent years Boolean Networks (BN) and Probabilistic Boolean Networks (PBN) have become popular paradigms for modeling gene regulation. A PBN is a collection of BNs in which the gene state vector transitions according to the rules of one of the constituent BNs, and the network choice is governed by a selection distribution. Intervention in the context of PBNs was first proposed with an objective of avoid- ing undesirable states, such as those associated with a disease. The early methods of intervention were ad hoc, using concepts like mean first passage time and alteration of rule based str

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Biane, Célia. "Reprogrammation comportementale : modèles, algorithmes et application aux maladies complexes." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLE050.

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Les maladies complexes comme le Cancer et la maladie d'Alzheimer sont causées par des perturbations moléculaires multiples responsables d'un comportement cellulaire pathologique.Un enjeu majeur de la médecine de précision est l'identification des perturbations moléculaires induites par les maladies complexes et les thérapies à partir de leurs conséquences sur les phénotypes cellulaire.Nous définissons un modèle des maladies complexes,appelé la reprogrammation comportementale,assimilant les perturbations moléculaires à des altérations des fonctions dynamiques locales de systèmes dynamiques disc

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Ghaffari, Noushin. "Genomic Regulatory Networks, Reduction Mappings and Control." Thesis, 2012. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10726.

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All high-level living organisms are made of small cell units, containing DNA, RNA, genes, proteins etc. Genes are important components of the cells and it is necessary to understand the inter-gene relations, in order to comprehend, predict and ultimately intervene in the cells’ dynamics. Genetic regulatory networks (GRN) represent the gene interactions that dictate the cell behavior. Translational genomics aims to mathematically model GRNs and one of the main goals is to alter the networks’ behavior away from undesirable phenotypes such as cancer. The mathematical framework that has been often

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Bücher zum Thema "Control Boolean network"

Cheng, Daizhan, Hongsheng Qi, and Zhiqiang Li. Analysis and Control of Boolean Networks. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-097-7.

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R, Dougherty Edward, and Society for Industrial and Applied Mathematics., eds. Probabilistic boolean networks: The modeling and control of gene regulatory networks. Society for Industrial and Applied Mathematics, 2010.

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Shmulevich, Ilya. Probabilistic boolean networks: The modeling and control of gene regulatory networks. Society for Industrial and Applied Mathematics, 2010.

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Shmulevich, Ilya. Probabilistic boolean networks: The modeling and control of gene regulatory networks. Society for Industrial and Applied Mathematics, 2010.

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Shmulevich, Ilya. Probabilistic boolean networks: The modeling and control of gene regulatory networks. Society for Industrial and Applied Mathematics, 2010.

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Shmulevich, Ilya. Probabilistic boolean networks: The modeling and control of gene regulatory networks. Society for Industrial and Applied Mathematics, 2010.

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Zhang, Zhihua. Observer Design for Control and Fault Diagnosis of Boolean Networks. Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-35929-4.

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Cheng, Dai-Zhan. Analysis and control of boolean networks: A semi-tensor product approach. Springer, 2011.

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Li, Zhiqiang, Daizhan Cheng, and Hongsheng Qi. Analysis and Control of Boolean Networks. Springer, 2011.

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Tatsuya, Akutsu. Algorithms for Analysis, Inference, and Control of Boolean Networks. World Scientific Publishing Co Pte Ltd, 2018.

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Buchteile zum Thema "Control Boolean network"

Cheng, Daizhan, Hongsheng Qi, and Zhiqiang Li. "Topological Structure of a Boolean Network." In Communications and Control Engineering. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-097-7_5.

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Biane, Célia, and Franck Delaplace. "Abduction Based Drug Target Discovery Using Boolean Control Network." In Computational Methods in Systems Biology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67471-1_4.

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Cheng, Daizhan, Hongsheng Qi, and Zhiqiang Li. "Random Boolean Networks." In Communications and Control Engineering. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-097-7_19.

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Darke, Priyanka, Bharti Chimdyalwar, Sakshi Agrawal, Shrawan Kumar, R. Venkatesh, and Supratik Chakraborty. "VeriAbsL: Scalable Verification by Abstraction and Strategy Prediction (Competition Contribution)." In Tools and Algorithms for the Construction and Analysis of Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30820-8_41.

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AbstractWe present VeriAbsL, a reachability verifier that performs verification in three stages. First, it slices the input code using a combination of two slicers, then it verifies the slices using predicted strategies, and at last, it composes the result of verifying the individual slices. We introduce a novel shallow slicing technique that uses variable reference information of the program, and data and control dependencies of the entry function to generate slices. We also introduce a novel strategy prediction technique that uses machine learning to predict a strategy. It uses boolean featu

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Cheng, Daizhan, Hongsheng Qi, and Zhiqiang Li. "Realization of Boolean Control Networks." In Communications and Control Engineering. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-097-7_10.

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Cheng, Daizhan, Hongsheng Qi, and Zhiqiang Li. "Identification of Boolean Control Networks." In Communications and Control Engineering. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-097-7_17.

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Zhang, Kuize, Lijun Zhang, and Lihua Xie. "Observability of Boolean Control Networks." In Discrete-Time and Discrete-Space Dynamical Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25972-3_4.

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Zhang, Kuize, Lijun Zhang, and Lihua Xie. "Detectability of Boolean Control Networks." In Discrete-Time and Discrete-Space Dynamical Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25972-3_5.

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Li, Haitao, Xinrong Yang, and Wenrong Li. "Control Design of Logical Control Networks." In From Boolean Matrix Theory to Logical Dynamical Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2967-1_8.

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Taou, Nadia S., David W. Corne, and Michael A. Lones. "Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks." In Applications of Evolutionary Computation. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31204-0_23.

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Konferenzberichte zum Thema "Control Boolean network"

Zhang, Wenqing, Yunlei Zou, and Wenbing Zhang. "On Reducible States of Boolean Control Networks." In 2024 43rd Chinese Control Conference (CCC). IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10662756.

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Sutavani, S., K. Sarda, A. Yerudkar, and N. Singh. "Interpretation of complex reaction networks in Boolean network framework." In 2018 Indian Control Conference (ICC). IEEE, 2018. http://dx.doi.org/10.1109/indiancc.2018.8307945.

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Li, Zhiqiang, Huimin Xiao, and Jinli Song. "Uniformly partial stability of Boolean network." In 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6895597.

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He, Yun, and Junmi Li. "Observability of a temporal Boolean network." In 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6895632.

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Li, Zhiqiang, Jinli Song, and Jian Yang. "Partial stability of probabilistic Boolean network." In 2014 26th Chinese Control And Decision Conference (CCDC). IEEE, 2014. http://dx.doi.org/10.1109/ccdc.2014.6852489.

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Sridharan, S., R. Layek, A. Datta, and J. Venkatraj. "Boolean network model of oxidative stress response pathways." In 2012 American Control Conference - ACC 2012. IEEE, 2012. http://dx.doi.org/10.1109/acc.2012.6315168.

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Lin, Lin, and Jinde Cao. "Controllability of Switched Boolean Control Network via Sampled-Data Control." In 2019 Chinese Control Conference (CCC). IEEE, 2019. http://dx.doi.org/10.23919/chicc.2019.8865411.

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Sonam, K., S. Sutavani, S. R. Wagh, F. S. Kazi, and N. M. Singh. "Optimal Control of Probabilistic Boolean Network using Embedding Framework." In 2021 American Control Conference (ACC). IEEE, 2021. http://dx.doi.org/10.23919/acc50511.2021.9483140.

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Fangfei, Li, Zhao Shouwei, Li Chunxiang, and Yu Zhaoxu. "Partial stabilization for Boolean network with state feedback control." In 2015 34th Chinese Control Conference (CCC). IEEE, 2015. http://dx.doi.org/10.1109/chicc.2015.7259846.

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Chen, Xudong, Zuguang Gao, and Tamer Basar. "Asymptotic behavior of a reduced conjunctive Boolean network." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8264308.

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