scholarly journals The stability and Hopf bifurcation analysis of a gene expression model

2012 ◽  
Vol 395 (1) ◽  
pp. 103-113 ◽  
Author(s):  
Tonghua Zhang ◽  
Yongli Song ◽  
Hong Zang
Keyword(s):  
Gene Expression ◽  
Hopf Bifurcation ◽  
Bifurcation Analysis ◽  
Expression Model ◽  
The Stability ◽  
Gene Expression Model

scholarly journals Stability and Hopf Bifurcation Analysis of a Gene Expression Model with Diffusion and Time Delay

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yahong Peng ◽  
Tonghua Zhang
Keyword(s):  
Gene Expression ◽  
Hopf Bifurcation ◽  
Local Stability ◽  
Time Delays ◽  
Center Manifold ◽  
Hopf Bifurcations ◽  
Expression Model ◽  
The Stability ◽  
And Diffusion ◽  
Gene Expression Model

We consider a model for gene expression with one or two time delays and diffusion. The local stability and delay-induced Hopf bifurcation are investigated. We also derive the formulas determining the direction and the stability of Hopf bifurcations by calculating the normal form on the center manifold.

Hopf bifurcation analysis in a model of oscillatory gene expression with delay

2009 ◽  
Vol 139 (4) ◽  
pp. 879-895 ◽  
Author(s):  
Junjie Wei ◽  
Chunbo Yu
Keyword(s):  
Gene Expression ◽  
Hopf Bifurcation ◽  
Periodic Solutions ◽  
Normal Forms ◽  
Higher Dimensional ◽  
Expression Model ◽  
Oscillatory Gene Expression ◽  
Existence Of Periodic Solutions ◽  
The Stability ◽  
Gene Expression Model

The dynamics of a gene expression model with time delay are investigated. The investigation confirms that a Hopf bifurcation occurs due to the existence of stability switches when the delay varies. An explicit algorithm for determining the direction of the Hopf bifurcations and the stability of the bifurcating periodic solutions has been derived by using the theory of the centre manifold and the normal forms method. The global existence of periodic solutions has been established using a global Hopf bifurcation result by Wu and a Bendixson criterion for higher-dimensional ordinary differential equations due to Li and Muldowney.

TWO DIFFERENT APPROACHES FOR GENE EXPRESSION MODEL CONTROL

BIOMAT 2011 ◽  
2012 ◽  
pp. 153-177
Author(s):  
N. A. BARBOSA ◽  
H DÍAZ ◽  
A. RAMIREZ
Keyword(s):  
Gene Expression ◽  
Model Control ◽  
Expression Model ◽  
Gene Expression Model

scholarly journals Evaluation of Genotype-Based Gene Expression Model Performance: A Cross-Framework and Cross-Dataset Study

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1531
Author(s):  
Vânia Tavares ◽  
Joana Monteiro ◽  
Evangelos Vassos ◽  
Jonathan Coleman ◽  
Diana Prata
Keyword(s):  
Gene Expression ◽  
Frontal Cortex ◽  
Model Performance ◽  
Variation Method ◽  
Expression Model ◽  
The Brain ◽  
Gene Expression Model ◽  
And Training ◽  
Predict Gene Expression ◽  
Fold Cross Validation

Predicting gene expression from genotyped data is valuable for studying inaccessible tissues such as the brain. Herein we present eGenScore, a polygenic/poly-variation method, and compare it with PrediXcan, a method based on regularized linear regression using elastic nets. While both methods have the same purpose of predicting gene expression based on genotype, they carry important methodological differences. We compared the performance of expression quantitative trait loci (eQTL) models to predict gene expression in the frontal cortex, comparing across these frameworks (eGenScore vs. PrediXcan) and training datasets (BrainEAC, which is brain-specific, vs. GTEx, which has data across multiple tissues). In addition to internal five-fold cross-validation, we externally validated the gene expression models using the CommonMind Consortium database. Our results showed that (1) PrediXcan outperforms eGenScore regardless of the training database used; and (2) when using PrediXcan, the performance of the eQTL models in frontal cortex is higher when trained with GTEx than with BrainEAC.

scholarly journals Bifurcation Analysis in a Delayed Diffusive Leslie-Gower Model

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Shuling Yan ◽  
Xinze Lian ◽  
Weiming Wang ◽  
Youbin Wang
Keyword(s):  
Stability Analysis ◽  
Hopf Bifurcation ◽  
Normal Form ◽  
Bifurcation Analysis ◽  
Center Manifold ◽  
Neumann Boundary ◽  
Positive Equilibrium ◽  
Center Manifold Theorem ◽  
Normal Form Theorem ◽  
The Stability

We investigate a modified delayed Leslie-Gower model under homogeneous Neumann boundary conditions. We give the stability analysis of the equilibria of the model and show the existence of Hopf bifurcation at the positive equilibrium under some conditions. Furthermore, we investigate the stability and direction of bifurcating periodic orbits by using normal form theorem and the center manifold theorem.

scholarly journals Stability and Hopf Bifurcation Analysis on a Bazykin Model with Delay

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianming Zhang ◽  
Lijun Zhang ◽  
Chaudry Masood Khalique
Keyword(s):  
Hopf Bifurcation ◽  
Normal Form ◽  
Periodic Solutions ◽  
Bifurcation Analysis ◽  
Center Manifold ◽  
Positive Equilibrium ◽  
Hopf Bifurcations ◽  
Finite Delay ◽  
The Stability ◽  
Predator System

The dynamics of a prey-predator system with a finite delay is investigated. We show that a sequence of Hopf bifurcations occurs at the positive equilibrium as the delay increases. By using the theory of normal form and center manifold, explicit expressions for determining the direction of the Hopf bifurcations and the stability of the bifurcating periodic solutions are derived.

A Multidimensional Gene Expression Model that Accurately Predicts Tumor Response to Pembrolizumab or Nivolumab

2020 ◽  
Vol 106 (5) ◽  
pp. 1132-1133
Author(s):  
D. Adkins ◽  
J. Ley ◽  
N. LaFranzo ◽  
J. Hiken ◽  
I. Schillebeeckx ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Response ◽  
Expression Model ◽  
Gene Expression Model

scholarly journals The ATRA-21 gene-expression model predicts retinoid sensitivity in CEBPA double mutant, t(8;21) and inv(16) AML patients

2019 ◽  
Vol 9 (10) ◽  
Author(s):  
Marco Bolis ◽  
Mineko Terao ◽  
Linda Pattini ◽  
Enrico Garattini ◽  
Maddalena Fratelli
Keyword(s):  
Gene Expression ◽  
Double Mutant ◽  
Expression Model ◽  
Gene Expression Model
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