Sensitivity analysis of Wnt Signaling Pathway

Azam, Mark; Bhatti, Aamer Iqbal; Arshad, Ali; Babar, Muhammad Zeeshan

doi:10.1109/ibcast.2013.6512143

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…The local and global methods of sensitivity analysis in chemical kinetics were further studied in [14]. There are also some applications of sensitivity analysis of systems biology models in [15]- [21]. More recently, the methods of local sensitivity analysis have been used to identify the critical model elements for a kinetic model of nuclear receptor signalling, the reader can see further details about the method in [10] [11].…”

Section: Introductionmentioning

confidence: 99%

Identifying Critical Parameters in SIR Model for Spread of Disease

Khoshnaw¹,

Mohammad²,

Salih³

2017

OJMSi

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Calculating analytical approximate solutions for non-linear infectious disease models is a difficult task. Such models often require computational tools to analyse analytical approximate methods which appear in some theoretical and practical applications in systems biology. They represent key critical elements and give some approximate solutions for such systems. The SIR epidemic disease model is given as the non-linear system of ODE's. Then, we use a proper scaling to reduce the number of parameters. We suggest Elzaki transform method to find analytical approximate solutions for the simplified model. The technique plays an important role in calculating the analytical approximate solutions. The local and global dynamics of the model are also studied. An investigation of the behaviour at infinity was conducted via finding the lines and singular points at infinity. Model dynamic results are computed in numerical simulations using Pplane8 and SimBiology Toolbox for Mathlab. Results provide a good step forward for describing the model dynamics. More interestingly, the simplified model could be accurate, robust, and used by biologists for different purposes such as identifying critical model elements.

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Section: Introductionmentioning

confidence: 99%

Identifying Critical Parameters in SIR Model for Spread of Disease

Khoshnaw¹,

Mohammad²,

Salih³

2017

OJMSi

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Inference of complex reaction mechanisms applying model reduction techniques

Shahzad,

Mustafa,

Khoshnaw

2024

Phys. Scr.

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Both structural (number of species and reactions) and temporal (extremely diverse reaction rates) aspectsof complexity are considered when describing large chemical reaction networks. A consistent way to make modelreduction is to construct the invariant manifold, which describes the asymptotic system behavior. Preliminaryapproximations to SIM (Slow Invariant Manifold) are constructed using the model reduction techniques (MRTs): theQuasi-Equilibrium Manifold (QEM), the Spectral Quasi-Equilibrium Manifold (SQEM), and the Intrinsic Low-Dimension Manifold (ILDM). In this paper, the activities of the concerned species and the overall dynamics of thesystem are examined. Two examples are used to demonstrate the techniques: the Michaelis-Menten mechanism, whichis a single reaction mechanism, and a multi-route route reaction mechanism. The behavior of each species on theavailable route is covered separately. As a result, the reduced invariant solution curve of several approaches isillustrated, along with a comparison of these methods in various graphs. Sensitivity analysis is applied using theSimBiology toolbox in MATLAB to monitor the role of each parameter involved. All the results of model reductiontechniques are simulated through MATLAB.

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Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - part A

Sinha

2017

BMC Syst Biol

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BackgroundEver since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials, augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues.ResultsThis manuscript ∙ explores the strength of contributing factors in the signaling pathway, ∙ analyzes the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and ∙ investigates the deviations in fold changes in the recently found prevalence of psychophysical laws working in the pathway. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors obtained from static and time series expression profiles using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indices.ConclusionThe results show the advantage of using density based indices over variance based indices mainly due to the former’s employment of distance measures & the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced & contribute to the pathway, as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis & representations in higher dimensional spaces can facilitate in time based administration of target therapeutic drugs & reveal hidden biological information within colorectal cancer samples.

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Sensitivity analysis of Wnt Signaling Pathway

Cited by 3 publications

References 11 publications

Identifying Critical Parameters in SIR Model for Spread of Disease

Identifying Critical Parameters in SIR Model for Spread of Disease

Inference of complex reaction mechanisms applying model reduction techniques

Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - part A

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