Sliding mode controller–observer pair for p53 pathway
In this study, a sliding mode control (SMC) based robust non-linear technique is presented for the drug design of a control-oriented p53 model. The control input generated by conventional SMC is discontinuous; however, depending on the physical nature of the system, drug infusion needs to be continuous. Therefore, to obtain a smooth control signal, a dynamic SMC (DSMC) is designed. Moreover, the boundedness of the zero-dynamics is also proved. To make the model-based control design possible, the unknown states of the system are estimated using an equivalent control based, reduced-order sliding mode observer. The robustness...
Source: IET Systems Biology - July 19, 2019 Category: Biology Source Type: research

Mining conditions specific hub genes from RNA-Seq gene-expression data via biclustering and their application to drug discovery
In this study, the authors have introduced a new approach for identifying conditions specific hub genes from the RNA-Seq data using a biclustering algorithm. In the proposed approach, efficient ‘runibic’ biclustering algorithm, the concept of gene co-expression network and concept of protein–protein interaction network have been used for getting better performance. The result shows that the proposed approach extracts biologically significant conditions specific hub genes which play an important role in various biological processes and pathways. These conditions specific hub genes can be used as prognostic...
Source: IET Systems Biology - July 19, 2019 Category: Biology Source Type: research

Control strategy design for the anti-HBV mathematical model
In this study, an anti-HBV mathematical model is considered and its control strategy of the drug treatment is designed. Based on the Lyapunov theory, this study derives three main theorems to propose three different control strategies, respectively, for drug treatments $mlpar trpar $m(t) and $nlpar trpar $n(t), such that all states of the anti-HBV model can finally converge to the infection-free equilibrium point $E_1$E1 asymptotically. Especially, the designed drug treatment $mlpar trpar $m(t) or $nlpar trpar $n(t) is not a fixed value, but it is time-varying and dependent on states. In Theorem 1, the single drug treatmen...
Source: IET Systems Biology - July 19, 2019 Category: Biology Source Type: research

Contribution of time delays to p53 oscillation in DNA damage response
Although the oscillatory dynamics of the p53 network have been extensively studied, the understanding of the mechanism of delay-induced oscillations is still limited. In this paper, a comprehensive mathematical model of p53 network is studied, which contains two delayed negative feedback loops. By studying the model with and without explicit delays, the results indicate that the time delay of Mdm2 protein synthesis can well control the pulse shape but cannot induce p53 oscillation alone, while the time delay required for Wip1 protein synthesis induces a Hopf bifurcation to drive p53 oscillation. In addition, the synergy of...
Source: IET Systems Biology - July 19, 2019 Category: Biology Source Type: research

Identification of a time-varying intracellular signalling model through data clustering and parameter selection: application to NF-$kappa $κB signalling pathway induced by LPS in the presence of BFA
Developing a model for a signalling pathway requires several iterations of experimentation and model refinement to obtain an accurate model. However, the implementation of such an approach to model a signalling pathway induced by a poorly-known stimulus can become labour intensive because only limited information on the pathway is available beforehand to formulate an initial model. Therefore, a large number of iterations are required since the initial model is likely to be erroneous. In this work, a numerical scheme is proposed to construct a time-varying model for a signalling pathway induced by a poorly-known stimulus wh...
Source: IET Systems Biology - July 19, 2019 Category: Biology Source Type: research

Hilbert transform-based time-series analysis of the circadian gene regulatory network
In this work, the authors propose the Hilbert transform (HT)-based numerical method to analyse the time series of the circadian rhythms. They demonstrate the application of HT by taking both deterministic and stochastic time series that they get from the simulation of the fruit fly model Drosophila melanogaster and show how to extract the period, construct phase response curves, determine period sensitivity of the parameters to perturbations and build Arnold tongues to identify the regions of entrainment. They also derive a phase model that they numerically simulate to capture whether the circadian time series entrains to ...
Source: IET Systems Biology - July 19, 2019 Category: Biology Source Type: research

Activity assessment of small drug molecules in estrogen receptor using multilevel prediction model
The authors have proposed an efficient multilevel prediction model for better activity assessment to test whether certain chemical compounds can disrupt processes in the human body that may create negative health effects. Here, a computational method (in-silico) is proposed for the quality prediction of drugs in terms of their activity, activity score, potency, and efficacy for estrogen receptors (ERs) by using various physicochemical properties (molecular descriptors). PaDEL-Descriptor is used for features extraction. The ER dataset has 8481 drug molecules where 1084 are active, and 7397 are inactive, and each drug molecu...
Source: IET Systems Biology - June 11, 2019 Category: Biology Source Type: research

Robust multi-objective blood glucose control in Type-1 diabetic patient
In this study, an automatic robust multi-objective controller has been proposed for blood glucose (BG) regulation in Type-1 Diabetic Mellitus (T1DM) patient through subcutaneous route. The main objective of this work is to control the BG level in T1DM patient in the presence of unannounced meal disturbances and other external noises with a minimum amount of insulin infusion rate. The multi-objective output-feedback controller with H∞, H2 and pole-placement constraints has been designed using linear matrix inequality technique. The designed controller for subcutaneous insulin delivery was tested on in silico adult and...
Source: IET Systems Biology - June 11, 2019 Category: Biology Source Type: research

Cancer adjuvant chemotherapy prediction model for non-small cell lung cancer
This study aims at building a predictive model to identify who needs ACT treatment and who should avoid it. To this end, the authors propose an innovative method to identify NSCLC-related prognostic genes from microarray gene-expression datasets. They also propose a new model using gene-expression programming algorithm for ACT classification. The proposed model was evaluated on integrated microarray datasets from four institutes and compared with four representative methods: general regression neural network, decision tree, support vector machine and naive Bayes. Evaluation results demonstrated the effectiveness of the pro...
Source: IET Systems Biology - June 11, 2019 Category: Biology Source Type: research

Robust control of HIV infection by antiretroviral therapy: a super-twisting sliding mode control approach
Acquired immune deficiency syndrome is an epidemic infectious disease which is caused by the human immunodeficiency virus (HIV) and that has proliferated across worldwide. It has been a matter of concern for the scientific community to develop an antiretroviral therapy, which will prompt a rapid decline in viral abundance. With this motivation, this study proposes the design of a robust super twisting sliding mode controller based on output information for an uncertain HIV infection model. The control objective is to decrease the concentration of infected CD4+ T cells to a specified level by drug administration using only ...
Source: IET Systems Biology - June 11, 2019 Category: Biology Source Type: research

Effective sampling trajectory optimisation for sensitivity analysis of biological systems
Sensitivity analysis has been widely applied to study the biological systems, including metabolic networks, signalling pathways, and genetic circuits. The Morris method is a kind of screening sensitivity analysis approach, which can fast identify a few key factors from numerous biological parameters and inputs. The parameter or input space is randomly sampled to produce a very limited number of trajectories for the calculation of elementary effects. It is clear that the sampled trajectories are not enough to cover the whole uncertain space, which eventually causes unstable sensitivity measures. This paper presents a novel ...
Source: IET Systems Biology - June 11, 2019 Category: Biology Source Type: research

Modelling and simulation of photosynthetic activities in C3 plants as affected by CO2
CO2 concentration ([CO2]) in a greenhouse may be a limiting factor for plant growth. Current greenhouse CO2 control strategy usually depends on expert experience, which may control [CO2] in a moderate range but cannot make it optimal due to lack of considering plant photochemistry reactions. A state-space kinetic model structure covering major photosynthetic reactions as affected by CO2 is useful for [CO2] control strategy development in a greenhouse because modern control theories are usually based on state-space models. In this work, a state-space kinetic model structure for photosynthesis was built, which describes the ...
Source: IET Systems Biology - June 11, 2019 Category: Biology Source Type: research

MicroRNAs and their target mRNAs as potential biomarkers among smokers and non-smokers with lung adenocarcinoma
Lung adenocarcinoma is one of the major causes of mortality. Current methods of diagnosis can be improved through identification of disease specific biomarkers. MicroRNAs are small non-coding regulators of gene expression, which can be potential biomarkers in various diseases. Thus, the main objective of this study was to gain mechanistic insights into genetic abnormalities occurring in lung adenocarcinoma by implementing an integrative analysis of miRNAs and mRNAs expression profiles in the case of both smokers and non-smokers. Differential expression was analysed by comparing publicly available lung adenocarcinoma sample...
Source: IET Systems Biology - April 30, 2019 Category: Biology Source Type: research

Rehabilitation of the Parkinson's tremor by using robust adaptive sliding mode controller: a simulation study
One of the efficient methods in controlling the Parkinson's tremor is Deep Brain Stimulation (DBS) therapy. The stimulation of Basal Ganglia (BG) by DBS brings no feedback though the existence of feedback reduces the additional stimulatory signal delivered to the brain. So this study offers a new adaptive architecture of a closed-loop control system in which two areas of BG are stimulated simultaneously to decrease the following three indicators: hand tremor, the level of a delivered stimulation signal in the disease condition, and the level of a delivered stimulation signal in health condition to the disease condition. On...
Source: IET Systems Biology - March 22, 2019 Category: Biology Source Type: research

Robust observer based control for plasma glucose regulation in type 1 diabetes patient using attractive ellipsoid method
This paper deals with the design of robust observer based output feedback control law for the stabilisation of an uncertain nonlinear system and subsequently apply the developed method for the regulation of plasma glucose concentration in Type 1 diabetes (T1D) patients. The principal objective behind the proposed design is to deal with the issues of intra-patient parametric variation and non-availability of all state variables for measurement. The proposed control technique for the T1D patient model is based on the attractive ellipsoid method (AEM). The observer and controller conditions are obtained in terms of linear mat...
Source: IET Systems Biology - March 22, 2019 Category: Biology Source Type: research

Prediction of putative small molecules for manipulation of enriched signalling pathways in hESC-derived early cardiovascular progenitors by bioinformatics analysis
Human pluripotent stem cell-derived cardiovascular progenitor cells (CPCs) are considered as powerful tools for cardiac regenerative medicine and developmental study. Mesoderm posterior1+ (MESP1+) cells are identified as the earliest CPCs from which almost all cardiac cell types are generated. Molecular insights to the transcriptional regulatory factors of early CPCs are required to control cell fate decisions. Herein, the microarray data set of human embryonic stem cells (hESCs)-derived MESP1+ cells was analysed and differentially expressed genes (DEGs) were identified in comparison to undifferentiated hESCs and MESP1-neg...
Source: IET Systems Biology - March 22, 2019 Category: Biology Source Type: research

Identification of self-regulatory network motifs in reverse engineering gene regulatory networks using microarray gene expression data
Gene Regulatory Networks (GRNs) are reconstructed from the microarray gene expression data through diversified computational approaches. This process ensues in symmetric and diagonal interaction of gene pairs that cannot be modelled as direct activation, inhibition, and self-regulatory interactions. The values of gene co-expressions could help in identifying co-regulations among them. The proposed approach aims at computing the differences in variances of co-expressed genes rather than computing differences in values of mean expressions across experimental conditions. It adopts multivariate co-variances using principal com...
Source: IET Systems Biology - March 22, 2019 Category: Biology Source Type: research

Adaptive fractional-order blood glucose regulator based on high-order sliding mode observer
In this study, to estimate the states that are not directly available from the Bergman minimal model a high-order sliding mode observer is proposed. Then fractional calculus is combined with sliding mode control (SMC) for blood glucose regulation to create more robustness performance and make more degree of freedom and flexibility for the proposed method. Then an adaptive fractional-order SMC is proposed. The adaptive SMC protect controller against disturbance and uncertainties while the fractional calculus provides robust performance. Numerical simulation verifies that the proposed controllers have better performance in t...
Source: IET Systems Biology - March 22, 2019 Category: Biology Source Type: research

Control of depth of anaesthesia using fractional-order adaptive high-gain controller
This study presents a fractional-order adaptive high-gain controller for control of depth of anaesthesia. To determine the depth of anaesthesia, the bispectral index (BIS) is utilised. To attain the desired BIS, the propofol infusion rate (as the control signal) should be appropriately adjusted. The effect of the propofol on the human body is modelled with the pharmacokinetic–pharmacodynamic (PK/PD) model. Physical properties of the patient such as gender, age, height and a like determine the parameters of the PK/PD model. This necessitates us to employ an appropriate adaptive controller. To attain this goal, a fract...
Source: IET Systems Biology - February 22, 2019 Category: Biology Source Type: research

Switching control strategy for the HIV dynamic system with some unknown parameters
This study considers an HIV dynamic system model with some unknown parameters and unmeasurable CD8 + T cell count and proposes a switching control strategy to force all states of the system to achieve a healthy status. It is a switching form with two different drug therapies and is designed based on the Lyapunov function theory such that the states of the HIV system approach the health equilibrium asymptotically without the influence of unknown parameters and unmeasurable cell counts. The values of all states and drug concentrations are assured to be positive in the control process so that the control strateg...
Source: IET Systems Biology - February 22, 2019 Category: Biology Source Type: research

Prediction of drug synergy score using ensemble based differential evolution
Prediction of drug synergy score is an ill-posed problem. It plays an efficient role in the medical field for inhibiting specific cancer agents. An efficient regression-based machine learning technique has an ability to minimise the drug synergy prediction errors. Therefore, in this study, an efficient machine learning technique for drug synergy prediction technique is designed by using ensemble based differential evolution (DE) for optimising the support vector machine (SVM). Because the tuning of the attributes of SVM kernel regulates the prediction precision. The ensemble based DE employs two trial vector generation tec...
Source: IET Systems Biology - February 22, 2019 Category: Biology Source Type: research

Efficient anticorrelated variance reduction for stochastic simulation of biochemical reactions
We investigate the computational challenge of improving the accuracy of the stochastic simulation estimation by inducing negative correlation through the anticorrelated variance reduction technique. A direct application of the technique to the stochastic simulation algorithm (SSA), employing the inverse transformation, is not efficient for simulating large networks because its computational cost is similar to the sum of independent simulation runs. We propose in this study a new algorithm that employs the propensity bounds of reactions, introduced recently in their rejection-based SSA, to correlate and synchronise the traj...
Source: IET Systems Biology - February 22, 2019 Category: Biology Source Type: research

Parameter estimation of a meal glucose–insulin model for TIDM patients from therapy historical data
The effect of meal on blood glucose concentration is a key issue in diabetes mellitus because its estimation could be very useful in therapy decisions. In the case of type 1 diabetes mellitus (T1DM), the therapy based on automatic insulin delivery requires a closed-loop control system to maintain euglycaemia even in the postprandial state. Thus, the mathematical modelling of glucose metabolism is relevant to predict the metabolic state of a patient. Moreover, the eating habits are characteristic of each person, so it is of interest that the mathematical models of meal intake allow to personalise the glycaemic state of the ...
Source: IET Systems Biology - February 22, 2019 Category: Biology Source Type: research

Fuzzy controller design for breast cancer treatment based on fractal dimension using breast thermograms
In this study, three non-linear indices consist of compression, one-dimensional (1D) and two-dimensional (2D) fractal dimensions are used for the determination of the malignancy or benignity of cancer tumours in breast thermograms. On the other hand, by developing the high-precision infrared cameras as well as new methods of image processing, biomedical thermography images have found a prominent position among the others. Furthermore, cancerous tissue can be affected by the laser. In this study, in order to treat the cancerous lesion identified by breast thermograms, the laser parameters are designed. The basis of controll...
Source: IET Systems Biology - February 22, 2019 Category: Biology Source Type: research

Modelling and simulation of chlorophyll fluorescence from photosystem II as affected by temperature
Emission of chlorophyll fluorescence (ChlF) from photosystem II (PSII) is affected by both plant status and environmental conditions. In this work, a state space model structure for ChlF from PSII with temperature as a variable model parameter was developed to provide insights into the temperature effects on photosynthesis and greenhouse temperature control. Experiments were carried out at 20, 25, and 30°C to validate the capability and flexibility of the developed model structure. Simulations of ChlF emission were performed for different temperatures. The results demonstrated the effectiveness of the ChlF model struct...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Hierarchical parameter estimation of GRN based on topological analysis
Reverse engineering of gene regulatory network (GRN) is an important and challenging task in systems biology. Existing parameter estimation approaches that compute model parameters with the same importance are usually computationally expensive or infeasible, especially in dealing with complex biological networks.In order to improve the efficiency of computational modeling, the paper applies a hierarchical estimation methodology in computational modeling of GRN based on topological analysis. This paper divides nodes in a network into various priority levels using the graph-based measure and genetic algorithm. The nodes in t...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Modelling and simulation of photosystem II chlorophyll fluorescence transition from dark-adapted state to light-adapted state
Green houses play a vital role in modern agriculture. Artificial light illumination is very important in a green house. While light is necessary for plant growth, excessive light in a green house may not bring more profit and even damages plants. Developing a plant-physiology-based light control strategy in a green house is important, which implies that a state-space model on photosynthetic activities is very useful because modern control theories and techniques are usually developed according to model structures in the state space. In this work, a simplified model structure on photosystem II activities was developed with ...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Study of cohabitation and interconnection effects on normal and leukaemic stem cells dynamics in acute myeloid leukaemia
On the basis of recent studies, understanding the intimate relationship between normal and leukaemic stem cells is very important in leukaemia treatment. The authors' aim in this work is to clarify and assess the effect of coexistence and interconnection phenomenon on the healthy and cancerous stem cell dynamics. To this end, they perform the analysis of two time-delayed stem cell models in acute myeloid leukaemia. The first model is based on decoupled healthy and cancerous stem cell populations (i.e. there is no interaction between cell dynamics) and the second model includes interconnection between both population's dyna...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Identifying cancer-related microRNAs based on subpathways
MicroRNAs (miRNAs) are a class of small endogenous non-coding genes that play important roles in post-transcriptional regulation as well as other important biological processes. Accumulating evidence indicated that miRNAs were extensively involved in the pathology of cancer. However, determining which miRNAs are related to a specific cancer is problematic because one miRNA may target multiple genes and one gene may be targeted by multiple miRNAs. The authors proposed a new approach, named miR_SubPath, to identify cancer-associated miRNAs by three steps. The targeted genes were determined based on differentially expressed g...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Time-invariant biological networks with feedback loops: structural equation models and structural identifiability
In this study, the structural identifiability analysis problem of time-invariant linear structural equation models (SEMs) with feedback loops is addressed, resulting in a general and efficient solution. The key idea is to combine Mason's gain with Wright's path coefficient method to generate identifiability equations, from which identifiability matrices are then derived to examine the structural identifiability of every single unknown parameter. The proposed method does not involve symbolic or expensive numerical computations, and is applicable to a broad range of time-invariant linear SEMs with or without explicit latent ...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Cancers classification based on deep neural networks and emotional learning approach
In the present era, enormous factors contribute to causing cancer. So cancer classification cannot rely only on doctor's thoughts. As a result, intelligent algorithms concerning doctor's help are inevitable. Therefore, the authors are motivated to suggest a novel algorithm to classify three cancer datasets; colon, ALL-AML, and leukaemia cancers. Their proposed algorithm is based on the deep neural network and emotional learning process. First of all, by applying the principal component analysis, they had a feature reduction. Then, they used deep neural as a feature extraction. Then, they implemented different classifiers; ...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Identification of essential proteins based on a new combination of topological and biological features in weighted protein–protein interaction networks
The identification of essential proteins in protein-protein interaction (PPI) networks is not only important in understanding the process of cellular life but also useful in diagnosis and drug design. The network topology-based centrality measures are sensitive to noise of network. Moreover, these measures cannot detect low-connectivity essential proteins. The authors have proposed a new method using a combination of topological centrality measures and biological features based on statistical analyses of essential proteins and protein complexes. With incomplete PPI networks, they face the challenge of false-positive intera...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Dynamic optimal experimental design yields marginal improvement over steady-state results for computational maximisation of regulatory T-cell induction in ex vivo culture
The isolation of T cells, followed by differentiation into Regulatory T cells (Tregs), and re-transplantation into the body has been proposed as a therapeutic option for inflammatory bowel disease. A key requirement for making this a viable therapeutic option is the generation of a large population of Tregs. However, cytokines in the local microenvironment can impact the yield of Tregs during differentiation. As such, experimental design is an essential part of evaluating the importance of different cytokine concentrations for Treg differentiation. However, currently only single, constant concentrations of the cytokines ha...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Biological pest control using a model-based robust feedback
Biological control is the artificial manipulation of natural enemies of a pest for its regulation to densities below a threshold for economic damage. The authors address the biological control of a class of pest population models using a model-based robust feedback approach. The proposed control framework is based on a recursive cascade control scheme exploiting the chained form of pest population models and the use of virtual inputs. The robust feedback is formulated considering the non-linear model uncertainties via a simple and intuitive control design. Numerical results on three pest biological control problems show th...
Source: IET Systems Biology - November 30, 2018 Category: Biology Source Type: research

Topological alternate centrality measure capturing drug targets in the network of MAPK pathways
A new centrality of the nodes in the network is proposed called alternate centrality, which can isolate effective drug targets in the complex signalling network. Alternate centrality metric defined over the network substructure (four nodes - motifs). The nodes involving in alternative activation in the motifs gain in metric values. Targeting high alternative centrality nodes hypothesised to be destructive free to the network due to their alternative activation mechanism. Overlapping and crosstalk among the gene products in the conserved network of MAPK pathways selected for the study. In silico knock-out of high alternate ...
Source: IET Systems Biology - October 5, 2018 Category: Biology Source Type: research

Blood glucose regulation in type 1 diabetic patients: an adaptive parametric compensation control-based approach
Here, a direct adaptive control strategy with parametric compensation is adopted for an uncertain non-linear model representing blood glucose regulation in type 1 diabetes mellitus patients. The uncertain parameters of the model are updated by appropriate design of adaptation laws using the Lyapunov method. The closed-loop response of the plasma glucose concentration as well as external insulin infusion rate is analysed for a wide range of variation of the model parameters through extensive simulation studies. The result indicates that the proposed adaptive control scheme avoids severe hypoglycaemia and gives satisfactory ...
Source: IET Systems Biology - October 5, 2018 Category: Biology Source Type: research

Fold change based approach for identification of significant network markers in breast, lung and prostate cancer
Cancer belongs to a class of highly aggressive diseases and a leading cause of death in the world. With more than 100 types of cancers, breast, lung and prostate cancer remain to be the most common types. To identify essential network markers (NMs) and therapeutic targets in these cancers, the authors present a novel approach which uses gene expression data from microarray and RNA-seq platforms and utilises the results from this data to evaluate protein-protein interaction (PPI) network. Differentially expressed genes (DEGs) are extracted from microarray data using three different statistical methods in R, to produce a con...
Source: IET Systems Biology - October 5, 2018 Category: Biology Source Type: research

Bifurcation analysis of insulin regulated mTOR signalling pathway in cancer cells
Insulin induced mTOR signalling pathway is a complex network implicated in many types of cancers. The molecular mechanism of this pathway is highly complex and the dynamics is tightly regulated by intricate positive and negative feedback loops. In breast cancer cell lines, metformin has been shown to induce phosphorylation at specific serine sites in insulin regulated substrate of mTOR pathway that results in apoptosis over cell proliferation. The author models and performs bifurcation analysis to simulate cell proliferation and apoptosis in mTOR signalling pathway to capture the dynamics both in the presence and absence o...
Source: IET Systems Biology - October 5, 2018 Category: Biology Source Type: research

Non-normality can facilitate pulsing in biomolecular circuits
Non-normality can underlie pulse dynamics in many engineering contexts. However, its role in pulses generated in biomolecular contexts is generally unclear. Here, the authors address this issue using the mathematical tools of linear algebra and systems theory on simple computational models of biomolecular circuits. They find that non-normality is present in standard models of feedforward loops. They used a generalised framework and pseudospectrum analysis to identify non-normality in larger biomolecular circuit models, finding that it correlates well with pulsing dynamics. Finally, they illustrate how these methods can be ...
Source: IET Systems Biology - October 5, 2018 Category: Biology Source Type: research

Optimal sliding mode control of drug delivery in cancerous tumour chemotherapy considering the obesity effects
Different control strategies have been proposed for drug delivery in chemotherapy during recent years. These control algorithms are designed based on dynamic models of various orders. The order of the model depends on the number of effects considered in the model. In a recent model, the effect of obesity on the tumour progression and optimal control strategy in chemotherapy have been investigated in a fifth-order state-space model. However, the optimal controller is open loop and not robust to the common uncertainties of such biological system. Here, the sliding surface is obtained by the optimal trajectory and by consider...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Effect of external periodic signals and electromagnetic radiation on autaptic regulation of neuronal firing
An improved Hindmarsh-Rose (HR) neuron model, where the memristor is a bridge between membrane potential and magnetic flux, can be used to investigate the effect of periodic signals on autaptic regulation of neurons under electromagnetic radiation. Based on the improved HR model driven by periodic high-low-frequency current and electromagnetic radiation, the responses of electrical autaptic regulation with diverse high-low-frequency signals are investigated using bifurcation analysis. It is found that the electrical modes of neurons are determined by the selecting parameters of both periodic high and low-frequency current ...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Hybrid CME–ODE method for efficient simulation of the galactose switch in yeast
It is well known that stochasticity in gene expression is an important source of noise that can have profound effects on the fate of a living cell. In the galactose genetic switch in yeast, the unbinding of a transcription repressor is induced by high concentrations of sugar particles activating gene expression of sugar transporters. This response results in high propensity for all reactions involving interactions with the metabolite. The reactions for gene expression, feedback loops and transport are typically described by chemical master equations (CME). Sampling the CME using the stochastic simulation algorithm (SSA) re...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Gene expression feature selection for prostate cancer diagnosis using a two-phase heuristic–deterministic search strategy
Here, a two-phase search strategy is proposed to identify the biomarkers in gene expression data set for the prostate cancer diagnosis. A statistical filtering method is initially employed to remove the noisiest data. In the first phase of the search strategy, a multi-objective optimisation based on the binary particle swarm optimisation algorithm tuned by a chaotic method is proposed to select the optimal subset of genes with the minimum number of genes and the maximum classification accuracy. Finally, in the second phase of the search strategy, the cache-based modification of the sequential forward floating selection alg...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Optimal neuro-fuzzy control of hepatitis C virus integrated by genetic algorithm
Hepatitis C blood born virus is a major cause of liver disease that more than three per cent of people in the world is dealing with, and the spread of hepatitis C virus (HCV) infection in different populations is one of the most important issues in epidemiology. In the present study, a new intelligent controller is developed and tested to control the hepatitis C infection in the population which the authors refer to as an optimal adaptive neuro-fuzzy controller. To design the controller, some data is required for training the employed adaptive neuro-fuzzy inference system (ANFIS) which is selected by the genetic algorithm....
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Algorithm to identify the optimal perturbation based on the net basin-of-state of perturbed states in Boolean network
Boolean networks are widely used to model gene regulatory networks and to design therapeutic intervention strategies to affect the long-term behavior of systems. Here, the authors investigate the 1 bit perturbation, which falls under the category of structural intervention. The authors' idea is that, if and only if a perturbed state evolves from a desirable attractor to an undesirable attractor or from an undesirable attractor to a desirable attractor, then the size of basin of attractor of a desirable attractor may decrease or increase. In this case, if the authors obtain the net BOS of the perturbed states, they can quic...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Two-dimensional polynomial type canonical relaxation oscillator model for p53 dynamics
p53 network, which is responsible for DNA damage response of cells, exhibits three distinct qualitative behaviours; low state, oscillation and high state, which are associated with normal cell cycle progression, cell cycle arrest and apoptosis, respectively. The experimental studies demonstrate that these dynamics of p53 are due to the ATM and Wip1 interaction. This paper proposes a simple two-dimensional canonical relaxation oscillator model based on the identified topological structure of ATM and Wip1 interaction underlying these qualitative behaviours of p53 network. The model includes only polynomial terms that have th...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Observer-based resilient finite-time control of blood gases model during extra-corporeal circulation
This study aims at designing an observer-based resilient controller to regulate the amount of oxygen and carbon dioxide in the blood of patients during the extra-corporeal blood circulation process. More precisely, in this study, a suitable observer-based resilient controller is constructed to regulate the levels of patient blood gases in a finite interval of time. The finite-time boundedness with the prescribed H∞ performance index of the considered blood gases control system against modelling uncertainty and external disturbances is ensured by using Lyapunov stability analysis. Moreover, a set of sufficient conditi...
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Effective implicit finite-difference method for sensitivity analysis of stiff stochastic discrete biochemical systems
In this study, the authors present a novel method for estimation of sensitivity coefficients for CME models of biochemical reaction systems that span a wide range of time-scales. They make use of finite-difference approximations and adaptive implicit tau-leaping strategies to estimate sensitivities for these stiff models, resulting in significant computational efficiencies in comparison with previously published approaches of similar accuracy, as evidenced by illustrative applications. (Source: IET Systems Biology)
Source: IET Systems Biology - August 14, 2018 Category: Biology Source Type: research

Integrative computational approach to evaluate risk genes for postmenopausal osteoporosis
In recent years, numerous studies reported over a hundred of genes playing roles in the etiology of postmenopausal osteoporosis (PO). However, many of these candidate genes were lack of replication and results were not always consistent. Here, the authors proposed a computational workflow to curate and evaluate PO related genes. They integrate large-scale literature knowledge data and gene expression data (PO case/control: 10/10) for the marker evaluation. Pathway enrichment, sub-network enrichment, and gene–gene interaction analysis were conducted to study the pathogenic profile of the candidate genes, with four met...
Source: IET Systems Biology - May 15, 2018 Category: Biology Source Type: research

Structural analysis of a Petri net model of oxidative stress in atherosclerosis
In this study, a Petri net model of atherosclerosis regulation is presented. This model includes also some information about stoichiometric relationships between its components and covers all mentioned factors. For the model, a structural analysis based on invariants was made and biological conclusions are presented. Since the model contains inhibitor arcs, a heuristic method for analysis of such cases is presented. This method can be used to extend the concept of feasible t-invariants. (Source: IET Systems Biology)
Source: IET Systems Biology - May 15, 2018 Category: Biology Source Type: research