FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2950918453> ?p ?o ?g. }

• W2950918453 abstract "ABSTRACT In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data. AUTHOR SUMMARY Ordinary differential equation (ODE) based models are a popular approach for modelling biological networks. A limitation of ODE models is that they require complete networks and detailed kinetic parameterisation. An alternative is the use of discrete, executable models, in which nodes are assigned discrete value ranges, and the relationship between them defined with simple mathematical operations. One tool for constructing such models is the BioModelAnalyzer (BMA), an open source and publicly available ( https://www.biomodelanalyzer.org ) software, aimed to be fully usable by researchers without extensive computational or mathematical experience. A fundamental question for executable models is whether the high level of abstraction substantially reduces expressivity relative to continuous approaches. Here, we present a canonical library of biological signalling motifs, initially defined by Tyson et al (2003), translated for the first time into the BMA. We show that; 1) these motifs are easily and fully translatable from continuous to discrete models, 2) Combining these motifs in a computationally naïve way generates a fully functional and predictive model of the yeast cell cycle." @default.
• W2950918453 created "2019-06-27" @default.
• W2950918453 creator A5009370343 @default.
• W2950918453 creator A5027490511 @default.
• W2950918453 creator A5045161607 @default.
• W2950918453 creator A5047570415 @default.
• W2950918453 creator A5082726741 @default.
• W2950918453 creator A5086492427 @default.
• W2950918453 creator A5089344463 @default.
• W2950918453 date "2018-01-18" @default.
• W2950918453 modified "2023-09-23" @default.
• W2950918453 title "A Toolbox for Discrete Modelling of Cell Signalling Dynamics" @default.
• W2950918453 cites W1480236339 @default.
• W2950918453 cites W1486453207 @default.
• W2950918453 cites W1575657391 @default.
• W2950918453 cites W1788683850 @default.
• W2950918453 cites W1914412773 @default.
• W2950918453 cites W1962321933 @default.
• W2950918453 cites W1965130826 @default.
• W2950918453 cites W1968146089 @default.
• W2950918453 cites W1969154599 @default.
• W2950918453 cites W1971224531 @default.
• W2950918453 cites W1971908328 @default.
• W2950918453 cites W1981494266 @default.
• W2950918453 cites W1986397618 @default.
• W2950918453 cites W1993346355 @default.
• W2950918453 cites W2016019304 @default.
• W2950918453 cites W2028038938 @default.
• W2950918453 cites W2031369606 @default.
• W2950918453 cites W2034717053 @default.
• W2950918453 cites W2048069174 @default.
• W2950918453 cites W2059729638 @default.
• W2950918453 cites W2065949669 @default.
• W2950918453 cites W2073166133 @default.
• W2950918453 cites W2080457256 @default.
• W2950918453 cites W2084350197 @default.
• W2950918453 cites W2090341259 @default.
• W2950918453 cites W2096707214 @default.
• W2950918453 cites W2106362845 @default.
• W2950918453 cites W2108129909 @default.
• W2950918453 cites W2117392072 @default.
• W2950918453 cites W2122869170 @default.
• W2950918453 cites W2132626965 @default.
• W2950918453 cites W2133254839 @default.
• W2950918453 cites W2141436421 @default.
• W2950918453 cites W2144702196 @default.
• W2950918453 cites W2150750144 @default.
• W2950918453 cites W2159185219 @default.
• W2950918453 cites W2160145365 @default.
• W2950918453 cites W2276582555 @default.
• W2950918453 cites W2511763738 @default.
• W2950918453 cites W2566426512 @default.
• W2950918453 cites W4248881223 @default.
• W2950918453 doi "https://doi.org/10.1101/249888" @default.
• W2950918453 hasPublicationYear "2018" @default.
• W2950918453 type Work @default.
• W2950918453 sameAs 2950918453 @default.
• W2950918453 citedByCount "0" @default.
• W2950918453 crossrefType "posted-content" @default.
• W2950918453 hasAuthorship W2950918453A5009370343 @default.
• W2950918453 hasAuthorship W2950918453A5027490511 @default.
• W2950918453 hasAuthorship W2950918453A5045161607 @default.
• W2950918453 hasAuthorship W2950918453A5047570415 @default.
• W2950918453 hasAuthorship W2950918453A5082726741 @default.
• W2950918453 hasAuthorship W2950918453A5086492427 @default.
• W2950918453 hasAuthorship W2950918453A5089344463 @default.
• W2950918453 hasBestOaLocation W29509184531 @default.
• W2950918453 hasConcept C104317684 @default.
• W2950918453 hasConcept C127413603 @default.
• W2950918453 hasConcept C134306372 @default.
• W2950918453 hasConcept C146978453 @default.
• W2950918453 hasConcept C150194340 @default.
• W2950918453 hasConcept C160145156 @default.
• W2950918453 hasConcept C199360897 @default.
• W2950918453 hasConcept C2777655017 @default.
• W2950918453 hasConcept C28225019 @default.
• W2950918453 hasConcept C28826006 @default.
• W2950918453 hasConcept C33923547 @default.
• W2950918453 hasConcept C34862557 @default.
• W2950918453 hasConcept C37789001 @default.
• W2950918453 hasConcept C41008148 @default.
• W2950918453 hasConcept C51544822 @default.
• W2950918453 hasConcept C55493867 @default.
• W2950918453 hasConcept C60644358 @default.
• W2950918453 hasConcept C67339327 @default.
• W2950918453 hasConcept C78045399 @default.
• W2950918453 hasConcept C80444323 @default.
• W2950918453 hasConcept C86803240 @default.
• W2950918453 hasConcept C93226319 @default.
• W2950918453 hasConceptScore W2950918453C104317684 @default.
• W2950918453 hasConceptScore W2950918453C127413603 @default.
• W2950918453 hasConceptScore W2950918453C134306372 @default.
• W2950918453 hasConceptScore W2950918453C146978453 @default.
• W2950918453 hasConceptScore W2950918453C150194340 @default.
• W2950918453 hasConceptScore W2950918453C160145156 @default.
• W2950918453 hasConceptScore W2950918453C199360897 @default.
• W2950918453 hasConceptScore W2950918453C2777655017 @default.
• W2950918453 hasConceptScore W2950918453C28225019 @default.
• W2950918453 hasConceptScore W2950918453C28826006 @default.
• W2950918453 hasConceptScore W2950918453C33923547 @default.

• next