Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling.
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Logical Modeling and Dynamical Analysis of Cellular NetworksA Neutrophil Phenotype Model for Extracorporeal Treatment of SepsisSpatial analysis of expression patterns predicts genetic interactions at the mid-hindbrain boundaryQuantitative and logic modelling of molecular and gene networksIntegrating signals from the T-cell receptor and the interleukin-2 receptorTraining signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuliDiscovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical ModelingComputational models reduce complexity and accelerate insight into cardiac signaling networksModeling cardiac β-adrenergic signaling with normalized-Hill differential equations: comparison with a biochemical model.CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.Realistic control of network dynamics.Sharpening of expression domains induced by transcription and microRNA regulation within a spatio-temporal model of mid-hindbrain boundary formationData-driven reverse engineering of signaling pathways using ensembles of dynamic models.Modeling hormonal control of cambium proliferationOdefy--from discrete to continuous models.Continuous variables logic via coupled automata using a DNAzyme cascade with feedbackDiscrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction.Analysis of cell adhesion during early stages of colon cancer based on an extended multi-valued logic approach.Ensemble models of neutrophil trafficking in severe sepsis.Stochastic Boolean networks: an efficient approach to modeling gene regulatory networks.Levels of pro-apoptotic regulator Bad and anti-apoptotic regulator Bcl-xL determine the type of the apoptotic logic gate.Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeastJimena: efficient computing and system state identification for genetic regulatory networks.Model checking to assess T-helper cell plasticity.BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.Multiple model-informed open-loop control of uncertain intracellular signaling dynamicsAngiogenic activity of breast cancer patients' monocytes reverted by combined use of systems modeling and experimental approachesAnalysis of transcription factor network underlying 3T3-L1 adipocyte differentiation.Cell fate reprogramming by control of intracellular network dynamics.A Semiquantitative Framework for Gene Regulatory Networks: Increasing the Time and Quantitative Resolution of Boolean Networks.Systems medicine: evolution of systems biology from bench to bedsideLogical-continuous modelling of post-translationally regulated bistability of curli fiber expression in Escherichia coli.Predicting Variabilities in Cardiac Gene Expression with a Boolean Network Incorporating UncertaintyA Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle.Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells.Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approachControl of Stochastic and Induced Switching in Biophysical NetworksSimulation of the dynamics of primary immunodeficiencies in CD4+ T-cells.Boolean model of yeast apoptosis as a tool to study yeast and human apoptotic regulationsA geometrical approach to control and controllability of nonlinear dynamical networks.
P2860
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P2860
Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling.
description
2009 nî lūn-bûn
@nan
2009 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年学术文章
@wuu
2009年学术文章
@zh-cn
2009年学术文章
@zh-hans
2009年学术文章
@zh-my
2009年学术文章
@zh-sg
2009年學術文章
@yue
name
Transforming Boolean models to ...... to T-cell receptor signaling.
@ast
Transforming Boolean models to ...... to T-cell receptor signaling.
@en
type
label
Transforming Boolean models to ...... to T-cell receptor signaling.
@ast
Transforming Boolean models to ...... to T-cell receptor signaling.
@en
prefLabel
Transforming Boolean models to ...... to T-cell receptor signaling.
@ast
Transforming Boolean models to ...... to T-cell receptor signaling.
@en
P2860
P50
P356
P1433
P1476
Transforming Boolean models to ...... to T-cell receptor signaling.
@en
P2093
Dominik M Wittmann
Jan Krumsiek
P2860
P2888
P356
10.1186/1752-0509-3-98
P577
2009-09-28T00:00:00Z
P5875
P6179
1005724038