Sensitivity analysis approaches applied to systems biology models

Zi, Zhike

doi:10.1049/iet-syb.2011.0015

Cited by 339 publications

(295 citation statements)

References 87 publications

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“…These are sensitivity analysis and uncertainty analysis. The sensitivity analysis is performed in order to identify variations in results obtained from original and perturbed model input values [34], [36]. It is the study of how the individual uncertainty of model input contributes to the overall uncertainty of a model output [14], [26].…”

Section: B Uncertainty Handling In Requirements Selection and Optimimentioning

confidence: 99%

Exact Analysis for Next Release Problem

Li¹

2016

2016 IEEE 24th International Requirements Engineering Conference (RE)

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Abstract-In software engineering, determining the set of requirements to implement in the next release is a critical foundation for the success of a project. Inappropriately including or excluding requirements may result in products that fail to satisfy stakeholders' needs, and might cause loss of revenue. In the meantime, uncertainty is characterised by incomplete understanding. It is inevitable in the early phase of requirements engineering, and could lead to unsound requirement decisions. To ease the impact of uncertainty in the software development process, it is important to provide techniques that explicitly manage uncertainty in requirements analysis and optimisation.This proposed research aims to provide a decision support framework for analysing uncertainty in requirements selection and optimisation. The proposed research involves three stages. Firstly, a simulation optimisation technique is introduced to model requirements uncertainty in requirements optimisation. Then, an exact technique is designed to eliminate the algorithmic uncertainty. Lastly, a probabilistic uncertainty analysis is applied to help the decision maker to understand requirement uncertainty propagation and the characteristics of requirements in requirements selection process.

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Section: B Uncertainty Handling In Requirements Selection and Optimimentioning

confidence: 99%

Exact Analysis for Next Release Problem

Li¹

2016

2016 IEEE 24th International Requirements Engineering Conference (RE)

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“…concentration of a metabolite) and the perturbation on parameters (e.g. Michaelis constant of an enzyme) are computed, which reflect the sensitivity of the model on a parameter [33,34]. Since, MEP pathway model was built with significant amount of data taken from other organisms (in cases where the values were unavailable for P. falciparum), sensitivity analysis becomes critical in assessing the results obtained from the simulations of this model.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Methylerythritol phosphate pathway to isoprenoids: Kinetic modeling andin silicoenzyme inhibitions inPlasmodium falciparum

Singh¹,

Ghosh²

2013

FEBS Letters

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a b s t r a c tThe methylerythritol phosphate (MEP) pathway of Plasmodium falciparum (P. falciparum) has become an attractive target for anti-malarial drug discovery. This study describes a kinetic model of this pathway, its use in validating 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) as drug target from the systemic perspective, and additional target identification, using metabolic control analysis and in silico inhibition studies. In addition to DXR, 1-deoxy-D-xylulose 5-phosphate synthase (DXS) can be targeted because it is the first enzyme of the pathway and has the highest flux control coefficient followed by that of DXR. In silico inhibition of both enzymes caused large decrement in the pathway flux. An added advantage of targeting DXS is its influence on vitamin B1 and B6 biosynthesis. Two more potential targets, 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase and 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase, were also identified. Their inhibition caused large accumulation of their substrates causing instability of the system. This study demonstrates that both types of enzyme targets, one acting via flux reduction and the other by metabolite accumulation, exist in P. falciparum MEP pathway. These groups of targets can be exploited for independent anti-malarial drugs.

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“…Parameter sensitivity analysis (PSA) is a common systems analysis that is used to elucidate the dependence of system behavior on system parameters [24][25][26][27]. In the PSA, we compute sensitivity coefficients whose magnitudes describe how much system states vary with changes in one or a combination of system parameters.…”

Section: Introductionmentioning

confidence: 99%

Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

Perumal

2018

Processes

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Studies performed at single-cell resolution have demonstrated the physiological significance of cell-to-cell variability. Various types of mathematical models and systems analyses of biological networks have further been used to gain a better understanding of the sources and regulatory mechanisms of such variability. In this work, we present a novel sensitivity analysis method, called molecular density function perturbation (MDFP), for the dynamical analysis of cellular heterogeneity. The proposed analysis is based on introducing perturbations to the density or distribution function of the cellular state variables at specific time points, and quantifying how such perturbations affect the state distribution at later time points. We applied the MDFP analysis to a model of a signal transduction pathway involving TRAIL (tumor necrosis factor-related apoptosis-inducing ligand)-induced apoptosis in HeLa cells. The MDFP analysis shows that caspase-8 activation regulates the timing of the switch-like increase of cPARP (cleaved poly(ADP-ribose) polymerase), an indicator of apoptosis. Meanwhile, the cell-to-cell variability in the commitment to apoptosis depends on mitochondrial outer membrane permeabilization (MOMP) and events following MOMP, including the release of Smac (second mitochondria-derived activator of caspases) and cytochrome c from mitochondria, the inhibition of XIAP (X-linked inhibitor of apoptosis) by Smac, and the formation of the apoptosome.

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Sensitivity analysis approaches applied to systems biology models

Cited by 339 publications

References 87 publications

Exact Analysis for Next Release Problem

Exact Analysis for Next Release Problem

Methylerythritol phosphate pathway to isoprenoids: Kinetic modeling andin silicoenzyme inhibitions inPlasmodium falciparum

Elucidating Cellular Population Dynamics by Molecular Density Function Perturbations

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