21 papers · ranked by Valyu relevance
István Albert, Juilee Thakar, Song Li, Ranran Zhang + 1 more
Modern life sciences research increasingly relies on computational solutions, from large scale data analyses to theoretical modeling. Within the theoretical models Boolean networks occupy an increasing role as they are eminently suited at mapping biological observations and hypotheses into a mathematical formalism. The…
David Murrugarra, Alan Veliz-Cuba, Boris Aguilar, Reinhard Laubenbacher
'Reinhard Laubenbacher'] Background Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such…
David Murrugarra, Alan Veliz-Cuba, Elena Dimitrova, Claus Kadelka + 2 more
'Matthew Wheeler' 'Reinhard Laubenbacher'] The concept of control is crucial for effectively understanding and applying biological network models. Key structural features relate to control functions through gene regulation, signaling, or metabolic mechanisms, and computational models need to encode these. Applications…
David Murrugarra, Alan Veliz-Cuba, Elena Dimitrova, Claus Kadelka + 2 more
'Matthew Wheeler' 'Reinhard Laubenbacher'] The concept of control is crucial for effectively understanding and applying biological network models. Key structural features relate to control functions through gene regulation, signaling, or metabolic mechanisms, and computational models need to encode these. Applications…
Rion B. Correia, Alexander J. Gates, Xuan Wang, Luis M. Rocha
Logical models offer a simple but powerful means to understand the complex dynamics of biochemical regulation, without the need to estimate kinetic parameters. However, even simple automata components can lead to collective dynamics that are computationally intractable when aggregated into networks. In previous work we…
Van-Giang Trinh, Kyu Hyong Park, Samuel Pastva, Jordan C Rozum
Boolean networks are popular dynamical models of cellular processes in systems biology. Their attractors model phenotypes that arise from the interplay of key regulatory subcircuits. A succession diagram describes this interplay in a discrete analog of Waddington’s epigenetic attractor landscape that allows for fast…
Julian D. Schwab, Hans A. Kestler
A common approach to address biological questions in systems biology is to simulate regulatory mechanisms using dynamic models. Among others, Boolean networks can be used to model the dynamics of regulatory processes in biology. Boolean network models allow simulating the qualitative behavior of the modeled processes.…
Michael P Verdicchio, Seungchan Kim
Motivation A grand challenge in the modeling of biological systems is the identification of key variables which can act as targets for intervention. Boolean networks are among the simplest of models, yet they have been shown to adequately model many of the complex dynamics of biological systems. In our recent work, we…
Cui Su, Jun Pang
We study the target control of asynchronous Boolean networks, to identify efficacious interventions that can drive the dynamics of a given Boolean network from any initial state to the desired target attractor. Based on the application time, the control can be realised with three types of perturbations, including…
Gustavo Maganã López, Laurence Calzone, Andrei Zinovyev, Loïc Paulevé
Boolean networks are largely employed to model the qualitative dynamics of cell fate processes by describing the change of binary activation states of genes and transcription factors with time. Being able to bridge such qualitative states with quantitative measurements of gene expressions in cells, as scRNA-Seq, is a…
Arnaud Poret, Claudio Monteiro, Jean‐Pierre Boissel
Due to the scarcity of quantitative details about biological phenomena, quantitative modeling in systems biology can be compromised, especially at the subcellular scale. One way to get around this is qualitative modeling because it requires few to no quantitative information. One of the most popular qualitative…
Jie Sun, Abd AlRahman R. AlMomani, Erik M. Bollt
Boolean functions and networks are commonly used in the modeling and analysis of complex biological systems, and this paradigm is highly relevant in other important areas in data science and decision making, such as in the medical field and in the finance industry. In a Boolean model, the truth state of a variable is…
Sergi Valverde
The presence of modular organization is a common property of a wide range of complex systems, from cellular or brain networks to technological graphs. Modularity allows some degree of segregation between different parts of the network and has been suggested to be a prerequisite for the evolvability of biological…
Matthew T. Wheeler, Claus Kadelka, Alan Veliz‐Cuba, David Murrugarra + 1 more
'Reinhard Laubenbacher'] Boolean networks have been used in a variety of settings, as models for general complex systems as well as models of specific systems in diverse fields, such as biology, engineering, and computer science. Traditionally, their properties as dynamical systems have been studied through simulation…
Antonio Bensussen, J. Arturo Arciniega-González, Elena R. Álvarez-Buylla, Juan Carlos Martínez-García
Characterizing the minimum, necessary and sufficient components to generate the dynamics of a biological system has always been a priority to understand its functioning. In this sense, the canonical form of biological systems modeled by Boolean networks accurately defines the components in charge of controlling the…
Karthik Chandrasekhar, Claus Kadelka, Reinhard Laubenbacher, David Murrugarra
'David Murrugarra'] Stability is an important characteristic of network models that has implications for other desirable aspects such as controllability. The stability of a Boolean network (BN) depends on various factors, such as the topology of its wiring diagram and the type of the functions describing its dynamics.…
Yi Zou
To model biological systems using networks, it is desirable to allow more than two levels of expression for the nodes and to allow the introduction of parameters. Various modeling and simulation methods addressing these needs using Boolean models, both synchronous and asynchronous, have been proposed in the literature.…
Kevin M. Stoltz, Cliff Joslyn
Boolean networks are a valuable class of discrete dynamical systems models, but they remain fundamentally limited by their inability to capture multi-way interactions in their components. To remedy this limitation, we propose a model of Boolean hypernetworks, which generalize standard Boolean networks. Utilizing the…
Gang Yang, Jorge G. T. Zañudo, Réka Albert
Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies. Network control, and its special case of target control, is a promising avenue toward developing disease therapies. In target control it is assumed that a small…
Wenpin Hou, Peiying Ruan, Wai-Ki Ching, Tatsuya Akutsu
It is known that many driver nodes are required to control complex biological networks. Previous studies imply that O(N) driver nodes are required in both linear complex network and Boolean network models with N nodes if an arbitrary state is specified as the target. In this paper, we mathematically prove under a…
Bingyu Jiang, Pierre Klemmer, Marek Ostaszewski
Boolean networks have become essential tools for modeling gene regulatory systems and understanding cellular decision-making processes, but their optimization for biological relevance remains challenging. This study presents a comprehensive benchmark comparison of three prominent Boolean network optimization…