Results 21 to 30 of about 11,341,390 (298)
Frontiers in Genetics, 2019 Complex cellular processes, such as phenotype decision making, are exceedingly difficult to analyze experimentally, due to the multiple-layer regulation of gene expression and the intercellular variability referred to as biological noise.
Marilisa Cortesi +5 more
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Evolving sensitivity balances Boolean networks [PDF]
, 2012 We investigate the sensitivity of Boolean Networks (BNs) to mutations. We are interested in Boolean Networks as a model of Gene Regulatory Networks (GRNs). We adopt Ribeiro and Kauffman’s Ergodic Set and use it to study the long term dynamics of a BN. We
Turner, Matthew S. +9 more
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Perbandingan Boolean Model Dan Vector Space Model Dalam Pencarian Dokumen Teks
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi, 2020 Perkembangan teknologi informasi di era globalisasi saat ini, membuat semua aspek kehidupan kita berubah dan tidak dapat dihindarkan dari pengaruh kemajuan zaman.
Susanti Susanti +4 more
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An Evaluation of Methods for Inferring Boolean Networks from Time-Series Data. [PDF]
PLoS ONE, 2013 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 ...
Natalie Berestovsky, Luay Nakhleh
doaj +1 more source
Unique coverage in Boolean models [PDF]
Statistics & Probability Letters, 2017 Consider a wireless cellular network consisting of small, densely scattered base stations. A user $u$ is {\em uniquely covered} by a base station $b$ if $u$ is the only user within distance $r$ of $b$. This makes it possible to assign the user $u$ to the base station $b$ without interference from any other user $u'$. We investigate the maximum possible
Martin Haenggi, Amites Sarkar
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Quantum algorithms for testing and learning Boolean functions [PDF]
, 2013 We discuss quantum algorithms based on the Bernstein-Vazirani algorithm for finding which input variables a Boolean function depends on. There are 2(n) possible linear Boolean functions of n input variables; given a linear Boolean function, the Bernstein-
Floess, Dominik +2 more
core +1 more source
Dynamics of Amyloid Beta Protein Signaling under Complexity Reduction: A Mathematical Modeling and BooleSim Simulation Approach [PDF]
EPJ Web of ConferencesUnderstanding how complex biological systems behave over time is essential for predicting their future states, especially when studying Alzheimer's disease.
Kociaj Inva, Çapuni Retina
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Mental models of Boolean concepts [PDF]
Cognitive Psychology, 2011 Negation, conjunction, and disjunction are major building blocks in the formation of concepts. This article presents a new model-based theory of these Boolean components. It predicts that individuals simplify the models of instances of concepts. Evidence corroborates the theory and challenges alternative accounts, such as those based on minimal ...
Geoffrey P, Goodwin, P N, Johnson-Laird
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Boolean network model predicts knockout mutant phenotypes of fission yeast. [PDF]
PLoS ONE, 2013 Boolean networks (ornetworks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene
Maria I Davidich, Stefan Bornholdt
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Model checking with Boolean Satisfiability [PDF]
Journal of Algorithms, 2008 The evolution of SAT algorithms over the last decade has motivated the application of SAT to model checking, initially through the use of SAT in bounded model checking and, more recently, in unbounded model checking. This paper provides an overview of modern SAT algorithms, SAT-based bounded model checking and some of the most promising approaches for ...
openaire +1 more source