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The concept of a nested canalizing Boolean function has been studied over the course of the last decade in the context of understanding the regulatory logic of molecular interaction networks, such as gene regulatory networks. Such functions…

动力系统 · 数学 2013-04-15 J. O. Adeyeye , C. Kadelka , R. Laubenbacher , Y. Li

Boolean network models of molecular regulatory networks have been used successfully in computational systems biology. The Boolean functions that appear in published models tend to have special properties, in particular the property of being…

动力系统 · 数学 2024-07-09 Yuan Li , John O. Adeyeye , David Murrugarra , Boris Aguilar , Reinhard Laubenbacher

Understanding design principles of molecular interaction networks is an important goal of molecular systems biology. Some insights have been gained into features of their network topology through the discovery of graph theoretic patterns…

分子网络 · 定量生物学 2013-01-18 David Murrugarra , Reinhard Laubenbacher

Inferring dynamic biochemical networks is one of the main challenges in systems biology. Given experimental data, the objective is to identify the rules of interaction among the different entities of the network. However, the number of…

交换代数 · 数学 2012-07-31 Franziska Hinkelmann , Abdul Salam Jarrah

This paper provides a collection of mathematical and computational tools for the study of robustness in nonlinear gene regulatory networks, represented by time- and state-discrete dynamical systems taking on multiple states. The focus is on…

动力系统 · 数学 2016-08-30 Claus Kadelka , Yuan Li , Jack Kuipers , John O. Adeyeye , Reinhard Laubenbacher

This paper focuses on the study of certain classes of Boolean functions that have appeared in several different contexts. Nested canalyzing functions have been studied recently in the context of Boolean network models of gene regulatory…

定量方法 · 定量生物学 2007-07-26 Abdul Salam Jarrah , Blessilda Raposa , Reinhard Laubenbacher

Canalization is a key organizing principle in complex systems, particularly in gene regulatory networks. It describes how certain input variables exert dominant control over a function's output, thereby imposing hierarchical structure and…

离散数学 · 计算机科学 2025-10-31 Claus Kadelka

This paper studies the mathematical properties of collectively canalizing Boolean functions, a class of functions that has arisen from applications in systems biology. Boolean networks are an increasingly popular modeling framework for…

离散数学 · 计算机科学 2023-06-07 Claus Kadelka , Benjamin Keilty , Reinhard Laubenbacher

We prove that nested canalizing functions are the minimum-sensitivity Boolean functions for any given activity ratio and we characterize the sensitivity boundary which has a nontrivial fractal structure. We further observe, on an extensive…

分子网络 · 定量生物学 2022-03-23 H. Coban , A. Kabakcioglu

The canalizing properties of biological functions have been mainly studied in the context of Boolean modelling of gene regulatory networks. An important mathematical consequence of canalization is a low average sensitivity, which ensures in…

组合数学 · 数学 2023-07-04 Élisabeth Remy , Paul Ruet

We introduce the nested canalyzing depth of a function, which measures the extent to which it retains a nested canalyzing structure. We characterize the structure of functions with a given depth and compute the expected activities and…

分子网络 · 定量生物学 2012-03-01 Lori Layne , Elena Dimitrova , Matthew Macauley

We prove that nested canalizing functions are the minimum-sensitivity Boolean functions for any activity ratio and we determine the functional form of this boundary which has a nontrivial fractal structure. We further observe that the…

分子网络 · 定量生物学 2024-08-14 Hamza Coban

Boolean networks are used to model biological networks such as gene regulatory networks. Often Boolean networks show very chaotic behavior which is sensitive to any small perturbations.In order to reduce the chaotic behavior and to attain…

系统与控制 · 计算机科学 2014-09-16 Camellia Ray , Jayanta Kumar Das , Pabitra Pal Choudhury

Canalizing functions have important applications in physics and biology. For example, they represent a mechanism capable of stabilizing chaotic behavior in Boolean network models of discrete dynamical systems. When comparing the class of…

数学物理 · 物理学 2009-11-10 Winfried Just , Ilya Shmulevich , John Konvalina

Boolean networks are used to model biological networks such as gene regulatory networks. Often Boolean networks show very chaotic behaviour which is sensitive to any small perturbations. In order to reduce the chaotic behaviour and to…

系统与控制 · 计算机科学 2014-09-25 Camellia Ray , Jayanta Kumar Das , Pabitra Pal Choudhury

Boolean network models have gained popularity in computational systems biology over the last dozen years. Many of these networks use canalizing Boolean functions, which has led to increased interest in the study of these functions. The…

离散数学 · 计算机科学 2015-04-29 Qijun He , Matthew Macauley

Canalization of genetic regulatory networks has been argued to be favored by evolutionary processes due to the stability that it can confer to phenotype expression. We explore whether a significant amount of canalization and partial…

定量方法 · 定量生物学 2009-11-13 C. J. Olson Reichhardt , Kevin E. Bassler

Many researchers have studied symmetry properties of various Boolean functions. A class of Boolean functions, called nested canalyzing functions (NCFs), has been used to model certain biological phenomena. We identify some interesting…

离散数学 · 计算机科学 2023-06-22 Daniel J. Rosenkrantz , Madhav V. Marathe , S. S. Ravi , Richard E. Stearns

We develop a general method to explore how the function performed by a biological network can constrain both its structural and dynamical network properties. This approach is orthogonal to prior studies which examine the functional…

分子网络 · 定量生物学 2009-11-13 Kai-Yeung Lau , Surya Ganguli , Chao Tang

Boolean networks are an important class of computational models for molecular interaction networks. Boolean canalization, a type of hierarchical clustering of the inputs of a Boolean function, has been extensively studied in the context of…

分子网络 · 定量生物学 2024-07-09 David Murrugarra , Elena S. Dimitrova
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