Browsing by Subject "Gene regulatory networks"

Now showing 1 - 8 of 8

Open Access
Chaos in gene regulatory networks: effects of time delays and interaction structure
(AIP Publishing LLC, 2024-03-01) Öztürk, Dilan; Atay, Fatihcan; Özbay, Hitay
In biological system models, gene expression levels are typically described by regulatory feedback mechanisms. Many studies of gene network models focus on dynamical interactions between components, but often overlook time delays. Here we present an extended model for gene regulatory networks with time delayed negative feedback, which is described by delay differential equations. We analyze nonlinear properties of the model in terms of chaos and compare the conditions with the benchmark homogeneous gene regulatory network model. Chaotic dynamics depend strongly on the inclusion of time delays, but the minimum motifs that show chaos differ when both original and extended models are considered. Our results suggest that, for a particular higher order extension of the gene network, it is possible to observe chaotic dynamics in a two-gene system without adding any self-inhibition. This finding can be explained as a result of modification of the original benchmark model induced by previously unmodeled dynamics. We argue that the inclusion of additional parameters in regulatory gene circuit models substantially enhances the likelihood of observing non-periodic dynamics.
Open Access
Distinct regulation of tonsillar immune response in virus infection
(Wiley-Blackwell Publishing Ltd., 2014) Jartti, T.; Palomares, O.; Waris, M.; Tastan, O.; Nieminen, R.; Puhakka, T.; Rückert, B.; Aab, A.; Vuorinen, T.; Allander, T.; Vahlberg, T.; Ruuskanen, O.; Akdis, M.; Akdis, C. A.
Background: The relationships between tonsillar immune responses, and viral infection and allergy are incompletely known. Objective To study intratonsillar/nasopharyngeal virus detections and in vivo expressions of T-cell- and innate immune response-specific cytokines, transcription factors, and type I/II/III interferons in human tonsils. Methods: Palatine tonsil samples were obtained from 143 elective tonsillectomy patients. Adenovirus, bocavirus-1, coronavirus, enteroviruses, influenza virus, metapneumovirus, parainfluenza virus, rhinovirus, and respiratory syncytial virus were detected using PCR. The mRNA expression levels of IFN-α, IFN-β, IFN-γ, IL-10, IL-13, IL-17, IL-28, IL-29, IL-37, TGF-β, FOXP3, GATA3, RORC2, and Tbet were directly analyzed by quantitative RT-PCR. Results Fifty percentage of subjects reported allergy, 59% had ≥1 nasopharyngeal viruses, and 24% had ≥1 intratonsillar viruses. Tonsillar virus detection showed a strong negative association with age; especially rhinovirus or parainfluenza virus detection showed positive association with IFN-γ and Tbet expressions. IL-37 expression was positively associated with atopic dermatitis, whereas IFN-α, IL-13, IL-28, and Tbet expressions were negatively associated with allergic diseases. Network analyses demonstrated strongly polarized clusters of immune regulatory (IL-10, IL-17, TGF-β, FOXP3, GATA3, RORC2, Tbet) and antiviral (IFN-α, IFN-β, IL-28, IL-29) genes. These two clusters became more distinctive in the presence of viral infection or allergy. A negative correlation between antiviral cytokines and IL-10, IL-17, IL-37, FOXP3, and RORC2 was observed only in the presence of viruses, and interestingly, IL-13 strongly correlated with antiviral cytokines. Conclusions: Tonsillar cytokine expression is closely related to existing viral infections, age, and allergic illnesses and shows distinct clusters between antiviral and immune regulatory genes. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Open Access
Essays on gene regulatory network models and their stability analysis
(2023-07) Şener, Dilan Öztürk
Gene expression is one of the core areas in comprehending and assessing how biological cells work. Gene regulatory networks (GRNs), representing the intri-cate mechanism between genes and their regulatory modules, are instrumental in controlling gene expression and cell functions. These models shed light on how transcription factors interact with their regulatory modules within a cell. Despite the multitude of studies focusing on the analysis and enhancement of GRNs, there is still room for contributions. This thesis investigates a novel framework inspired by the gene networks constructed using synthetic biology, and presents stability analyses of the nonlinear infinite dimensional dynamical system models arising in this framework. In the first part of the thesis, we extend a previously studied benchmark GRN model including time delay, and present an analysis of the extended frame-work. We utilize unmodeled dynamics and possibly ignored interactions, including higher-order dynamics, in our system design. The stability of the extended system is analyzed by considering various nonlinearity functions and design pa-rameters, and the results are compared with those of the benchmark original model. In the second part, we employ an extension of a gene network model using a multiplicative perturbation of the dynamical system. Each cascaded subsystem in this extended framework has an additional block, including a multiplicative term with a high-pass filter, and the effect of additional parameters on the robustness and delay margin of the system is investigated. Experiments with various design parameters yield that the stability characteristics of GRNs can be improved using the model pertaining to the extension under specific perturbations. Finally, the third part covers the analysis of nonlinear dynamics and chaos in GRNs, particularly focusing on the two-gene original and extended gene net-works. Chaotic dynamics depend strongly on the inclusion of time delays, but the circuit motifs that show chaos differ when both original and extended models are considered. Our results suggest that for a particular higher-order extension of the gene network, it is possible to observe the chaotic dynamics in a two-gene system without adding any self-inhibition. This finding can be explained as a result of the modification of the original benchmark model induced by unmodeled dynamics. We argue that regulatory gene circuit models with additional parameters demonstrate non-periodic dynamics much more easily.
Open Access
G-network modelling based abnormal pathway detection in gene regulatory networks
(Springer, London, 2012) Kim H.; Atalay, Rengül; Gelenbe, E.
Gene expression centered gene regulatory networks studies can provide insight into the dynamics of pathway activities that depend on changes in their environmental conditions. Thus we propose a new pathway analysis approach to detect differentially behaving pathways in abnormal conditions based on G-network theory. Using this approach gene regulatory network model parameters are estimated from normal and abnormal samples using optimization techniques with corresponding constraints. We show that in a "p53 network" application, the proposed method effectively detects anomalous activated/inactivated pathways related with MDM2, ATM/ATR and RB1 genes, which could not be observed from previous analyses of gene regulatory network normal and abnormal behaviour. © 2012 Springer-Verlag London Limited.
Open Access
Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal
(American Association for the Advancement of Science (A A A S), 2013) Gao J.; Aksoy, B. A.; Dogrusoz, U.; Dresdner, G.; Gross, B.; Sumer, S. O.; Sun, Y.; Jacobsen, A.; Sinha, R.; Larsson, E.; Cerami, E.; Sander, C.; Schultz, N.
The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics. © 2013 American Association for the Advancement of Science.
Open Access
Robustness and delay margin analysis of a gene regulatory network model
(Elsevier, 2022-10-10) Öztürk, Dilan; Özbay, Hitay; Atay, Fatihcan M.
In the past, a special type of nonlinear delay differential system structure was proposed for gene regulatory networks. For this cyclic dynamical system, stability analysis was done using various tools from systems theory. This paper investigates robust stability of an extended gene regulatory network model with time delayed negative feedback. Specifically, the delay margin analysis is done for this system under multiplicative uncertainty. The effect of uncertainty on the delay margin is determined. It is also shown that for particular higher order extensions of the model it is possible to improve the delay margin.
Open Access
A secant condition for cyclic systems with time delays and its application to Gene Regulatory Networks
(IFAC, 2015) Ahsen, M. E.; Özbay, Hitay; Niculescu, S. -I.
A stability condition is derived for cyclic systems with time delayed negative feedback. The result is an extension of the so-called secant condition, which is originally developed for systems without time delays. This extension of the secant condition gives a new local stability condition for a model of GRNs (Gene Regulatory Networks) under negative feedback. Stability robustness of homogenous networks is also investigated.
Open Access
Stability analysis of a dynamical model representing gene regulatory networks
(2012) Ahsen, M. E.; Özbay, Hitay; Niculescu, S. I.
In this paper we perform stability analysis of a class of cyclic biological processes involving time delayed feedback. More precisely, we analyze the genetic regulatory network having nonlinearities with negative Schwarzian derivatives. We derive a set of conditions implying global stability of the genetic regulatory network under positive feedback. As a special case, we also consider homogenous genetic regulatory networks and obtain an appropriate stability condition which depends only on the parameters of the nonlinearity function. © 2012 IFAC.