Phenotype control and elimination of variables in Boolean networks by Tonello, Elisa, Paulevé, Loïc

Subjects: “…Boolean networks, control, reduction, trap spaces…”
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Robust Invariant Set Analysis of Boolean Networks by Bowen Li, Jungang Lou, Yang Liu, Zhen Wang

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Effects of Antimodularity and Multiscale Influence in Random Boolean Networks by Luis A. Escobar, Hyobin Kim, Carlos Gershenson

“…We investigate the effects of modularity, antimodularity, and multiscale influence on random Boolean networks (RBNs). On the one hand, we produced modular, antimodular, and standard RBNs and compared them to identify how antimodularity affects the dynamical behaviors of RBNs. …”
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Reinforcement Learning with Probabilistic Boolean Network Models of Smart Grid Devices by Pedro Juan Rivera Torres, Carlos Gershenson García, María Fernanda Sánchez Puig, Samir Kanaan Izquierdo

“…In this paper, we showcase the application of a complex-adaptive, self-organizing modeling method, and Probabilistic Boolean Networks (PBNs), as a way towards the understanding of the dynamics of smart grid devices, and to model and characterize their behavior. …”
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Optimal Intervention in Semi-Markov-Based Asynchronous Probabilistic Boolean Networks by Qiuli Liu, Qingguo Zeng, Jinghao Huang, Deliang Li

“…Synchronous probabilistic Boolean networks (PBNs) and generalized asynchronous PBNs have received significant attention over the past decade as a tool for modeling complex genetic regulatory networks. …”
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A Multilayer Structure Facilitates the Production of Antifragile Systems in Boolean Network Models by Hyobin Kim, Omar K. Pineda, Carlos Gershenson

“…By comparing single-layer and multilayer Boolean networks based on our recently proposed antifragility measure, we found that the multilayer structure facilitated the production of antifragile systems. …”
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Marker and source-marker reprogramming of Most Permissive Boolean networks and ensembles with BoNesis by Paulevé, Loïc

“…Boolean networks (BNs) are discrete dynamical systems with applications to the modeling of cellular behaviors. …”
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A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks by Omar K. Pineda, Hyobin Kim, Carlos Gershenson

“…Here we propose a simply calculable measure of antifragility, based on the change of “satisfaction” before and after adding perturbations, and apply it to random Boolean networks (RBNs). Using the measure, we found that ordered RBNs are the most antifragile. …”
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Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization by Koichi Kobayashi, Kunihiko Hiraishi

“…In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. …”
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In-silico tool based on Boolean networks and meshless simulations for prediction of reaction and transport mechanisms in the systemic administration of chemotherapeutic drugs. by Fabián Mauricio Vélez Salazar, Iván David Patiño

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Technology independent optimization when implementing sparse systems of disjunctive normal forms of Boolean functions in ASIC by P. N. Bibilo, S. N. Kardash

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A Note on the Observability of Temporal Boolean Control Network by Wenping Shi, Bo Wu, Jing Han

“…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. …”
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Mathematical modeling in autoimmune diseases: from theory to clinical application by Yaroslav Ugolkov, Yaroslav Ugolkov, Yaroslav Ugolkov, Antonina Nikitich, Antonina Nikitich, Cristina Leon, Gabriel Helmlinger, Kirill Peskov, Kirill Peskov, Kirill Peskov, Kirill Peskov, Victor Sokolov, Victor Sokolov, Alina Volkova, Alina Volkova

“…. ≥70% of the models were developed as nonlinear systems of ordinary differential equations, others – as partial differential equations, integro-differential equations, Boolean networks, or probabilistic models. Despite covering a relatively wide range of diseases, most models described the same components of the immune system, such as T-cell response, cytokine influence, or the involvement of macrophages in autoimmune processes. …”
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Control of Cellular Differentiation Trajectories for Cancer Reversion by Jeong‐Ryeol Gong, Chun‐Kyung Lee, Hoon‐Min Kim, Juhee Kim, Jaeog Jeon, Sunmin Park, Kwang‐Hyun Cho

“…To tackle this problem, a computational framework, single‐cell Boolean network inference and control (BENEIN), is presented. …”
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Network analyses of brain tumor multiomic data reveal pharmacological opportunities to alter cell state transitions by Brandon Bumbaca, Jonah R. Huggins, Marc R. Birtwistle, James M. Gallo

“…These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. …”
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