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Search · four archives
26 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…
Julian D. Schwab, Silke D. Kühlwein, Nensi Ikonomi, Michael Kühl + 1 more
'Hans A. Kestler'] Title: Graphical abstract
Stefan Bornholdt, Stuart Kauffman
Genetic regulatory networks control ontogeny. For fifty years Boolean networks have served as models of such systems, ranging from ensembles of random Boolean networks as models for generic properties of gene regulation to working dynamical models of a growing number of sub-networks of real cells. At the same time…
José E.R. Cury, Patrícia Tenera Roxo, Vasco Manquinho, Claudine Chaouiya + 1 more
'Claudine Chaouiya' 'Pedro T. Monteiro'] Boolean networks constitute relevant mathematical models to study the behaviours of genetic and signalling networks. These networks define regulatory influences between molecular nodes, each being associated to a Boolean variable and a regulatory (local) function specifying its…
Natalie Berestovsky, Luay Nakhleh, Panayiotis V. Benos
Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in bioinformatics. Boolean networks have been used extensively for modeling…
Claus Kadelka, Taras-Michael Butrie, Evan Hilton, Jack Kinseth + 2 more
Gene regulatory networks (GRNs) play a central role in cellular decision-making. Understanding their structure and how it impacts their dynamics constitutes thus a fundamental biological question. GRNs are frequently modeled as Boolean networks, which are intuitive, simple to describe, and can yield qualitative results…
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…
Stéphanie Chevalier, Julia Becker, Yujuan Gui, Vincent Noël + 9 more
Boolean networks provide robust explainable and predictive models of cellular dynamics, especially for cellular differentiation and fate decision processes. Yet, the construction of such models is extremely challenging, as it requires integrating prior knowledge with experimental observation of transcriptome…
Žiga Pušnik, Miha Mraz, Nikolaj Zimic, Miha Moškon + 1 more
Boolean networks provide an effective mechanism for describing interactions and dynamics of gene regulatory networks (GRNs). Deriving accurate Boolean descriptions of GRNs is a challenging task. The number of experiments is usually much smaller than the number of genes. In addition, binarization leads to a loss of…
Claus Kadelka, Taras-Michael Butrie, Evan Hilton, Jack Kinseth + 2 more
'A. Schmidt' 'Haris Serdarevic'] Gene regulatory networks (GRNs) describe how a collection of genes governs the processes within a cell. Understanding how GRNs manage to consistently perform a particular function constitutes a key question in cell biology. GRNs are frequently modeled as Boolean networks, which are…
Yasharth Yadav, Ajay Subbaroyan, Olivier C. Martin, Areejit Samal
Boolean networks have been widely used to model gene networks. However, such models are coarse-grained to an extent that they abstract away molecular specificities of gene regulation. Alternatively, bipartite Boolean network models of gene regulation explicitly distinguish genes from transcription factors (TFs). In…
Claus Kadelka, Kishore Hari
The inference of gene regulatory networks (GRNs) from high-throughput data constitutes a fundamental and challenging task in systems biology. Boolean networks are a popular modeling framework to understand the dynamic nature of GRNs. In the absence of reliable methods to infer the regulatory logic of Boolean GRN…
Sara Sadat Aghamiri, Franck Delaplace
Recent developments in Omics-technologies revolutionized the investigation of biology by producing molecular data in multiple dimensions and scale. This breakthrough in biology raises the crucial issue of their interpretation based on modelling. In this undertaking, network provides a suitable framework for modelling…
Yasharth Yadav, Ajay Subbaroyan, Olivier C. Martin, Areejit Samal
Boolean network models have widely been used to study the dynamics of gene regulatory networks. However, such models are coarse-grained to an extent that they abstract away molecular specificities of gene regulation. In contrast, bipartite Boolean network models of gene regulation explicitly distinguish genes from…
Claus Kadelka, David Murrugarra
Biological networks, such as gene regulatory networks, possess desirable properties. They are more robust and controllable than random networks. This motivates the search for structural and dynamical features that evolution has incorporated into biological networks. A recent meta-analysis of published, expert-curated…
Shubham Tripathi, David A. Kessler, Herbert Levine
Regulatory networks as large and complex as those implicated in cell-fate choice are expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a macroscopically simple process. Additionally, regulatory network models are almost always incomplete and / or inexact, and do not…
Jordan C. Rozum, Colin Campbell, Eli Newby, Fatemeh Sadat Fatemi Nasrollahi + 1 more
'Fatemeh Sadat Fatemi Nasrollahi' 'Réka Albert'] Abstract: Interacting biological systems at all organizational levels display emergent behavior. Modeling these systems is made challenging by the number and variety of biological components and interactions (from molecules in gene regulatory networks to species in…
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…
Claus Kadelka, David Murrugarra
networks Authors: ['Claus Kadelka' 'David Murrugarra'] Biological networks such as gene regulatory networks possess desirable properties. They are more robust and controllable than random networks. This motivates the search for structural and dynamical features that evolution has incorporated in biological networks. 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…
A. S. Jereesh, V. K. Govindan
Bio-inspired algorithms are widely used to optimize the model parameters of GRN. In this paper, focus is given to develop improvised versions of bio-inspired algorithm for the specific problem of reconstruction of gene regulatory network. The approach is applied to the data set that was developed by the DNA microarray…
Authors not listed
Molecular mechanisms governing initiation steps of the assembly of thousands of endogenous multi-protein complexes (EMCs) remain incompletely understood. Here, multiple lines of observations are reported reflecting the biological functions-aligned initiation sequence of hybrid assembly pathways (HAPs) of EMCs. HAPs…
Hirotake Udono, Minzhi Fan, Yoko Saito, Hirohisa Ohno + 4 more
Programmable droplets, artificial liquid-like condensates of nucleic acids, are intelligent out-of-equilibrium systems that allow the critical aspects of their biological counterparts to be harnessed programmably, such as molecular sensing and phase-state change. While DNA has been central to the previous efforts, less…
Gergely Zahoránszky-Kőhalmi, Brandon Walker, Nathan Miller, Brett Yang + 11 more
The recent SmartGraph platform facilitates the execution of complex drug-discovery workflows with ease in the network-pharmacology paradigm. However, at the time of its publication, we identified the need for the development of an Application Programming Interface (API) that could promote biomedical data integration…
Aliye Hazal Koyuncu, Jacopo Movilli, Sevil Sahin, Dmitrii V. Kriukov + 2 more
This work describes a competing activation network, which is regulated by chemical feedback at the liquid-surface interface. Feedback loops dynamically tune the concentration of chemical components in living systems, thereby controlling regulatory processes in neural, genetic, and metabolic networks. Advances in…
Authors not listed
We present a chemical framework in which adaptive organization is achieved by tuning a gated quantum resonator (adaptive genomic resonator) {driven quantum oscillator} across a driven, dissipative reaction manifold (fitness landscape) {Hamiltonian potential surface}. In this view, catalytic elements set gain and phase…