Results 51 to 60 of about 20,901 (253)
A full bayesian approach for boolean genetic network inference. [PDF]
PLoS ONE, 2014 Boolean networks are a simple but efficient model for describing gene regulatory systems. A number of algorithms have been proposed to infer Boolean networks.
Shengtong Han +5 more
doaj +1 more source
Discrete and Continuous Dynamical Systems - S, 2011 Boolean networks are special types of finite state time-discrete dynamical systems. A Boolean network can be described by a function from an n-dimensional vector space over the field of two elements to itself. A fundamental problem in studying these dynamical systems is to link their long term behaviors to the structures of the functions that define ...
openaire +2 more sources
PLoS ONE, 2014 In this paper, we consider the Minimum Reaction Insertion (MRI) problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host
Wei Lu +3 more
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On the Design of Boolean Network Robots [PDF]
, 2011 Dynamical systems theory and complexity science provide powerful tools for analysing artificial agents and robots. Furthermore, they have been recently proposed also as a source of design principles and guidelines. Boolean networks are a prominent example of complex dynamical systems and they have been shown to effectively capture important phenomena ...
Andrea Roli +3 more
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Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
SAILoR: Structure-Aware Inference of Logic Rules.
PLoS ONEBoolean 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.
Žiga Pušnik +3 more
doaj +1 more source
An efficient algorithm for computing attractors of synchronous and asynchronous Boolean networks. [PDF]
PLoS ONE, 2013 Biological networks, such as genetic regulatory networks, often contain positive and negative feedback loops that settle down to dynamically stable patterns.
Desheng Zheng +5 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Edible electronics needs integrated logic circuits for computation and control. This work presents a potentially edible printed chitosan‐gated transistor with a design optimized for integration in circuits. Its implementation in integrated logic gates and circuits operating at low voltage (0.7 V) is demonstrated, as well as the compatibility with an ...
Giulia Coco +8 more
wiley +1 more source
From quantitative SBML models to Boolean networks
Applied Network Science, 2022 Modelling complex biological systems is necessary for their study and understanding. Biomodels is a repository of peer-reviewed models represented in the Systems Biology Markup Language (SBML).
Athénaïs Vaginay +2 more
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Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source