Efficient prediction of drug–drug interaction using deep learning models
A drug–drug interaction or drug synergy is extensively utilised for cancer treatment. However, prediction of drug–drug interaction is defined as an ill-posed problem, because manual testing is only implementable on small group of drugs. Predicting the drug–drug interaction score has been a popular research topic recently. Recently many machine learning models have proposed in the literature to predict the drug–drug interaction score efficiently. However, these models suffer from the over-fitting issue. Therefore, these models are not so-effective for predicting the drug–drug interaction score....
Source: IET Systems Biology - July 28, 2020 Category: Biology Source Type: research

Novel algebraic meal disturbance estimation based adaptive robust control design for blood glucose regulation in type 1 diabetes patients
This study designs a robust closed-loop control algorithm for elevated blood glucose level stabilisation in type 1 diabetic patients. The control algorithm is based on a novel control action resulting from integrating algebraic meal disturbance estimator with back-stepping integral sliding mode control (BISMC) technique. The estimator shows finite time convergence leading to accurate and fast estimation of meal disturbance. Moreover, compensation of the estimated disturbance in controller provides significant reduction in chattering phenomenon, which is inherent drawback of sliding mode control (SMC). The controller is app...
Source: IET Systems Biology - July 28, 2020 Category: Biology Source Type: research

Modelling and analysing biological oscillations in quorum sensing networks
Recent experiments have shown that the biological oscillation of quorum sensing (QS) system play a vital role not only in the process of bacterial synthesis but also in the treatment of cancer by releasing drugs. As known, these five substances TetR, CI, LacI, AiiA and AI are the core components of the QS system. However, the effects of AiiA and protein synthesis time delay on QS system are often ignored in the theoretical model, which is taken as a priority in the proposed research. Therefore, the authors developed a new mathematical model to explore the effects of AiiA and time delay on the dynamical behaviour of QS syst...
Source: IET Systems Biology - July 28, 2020 Category: Biology Source Type: research

Review of tools and algorithms for network motif discovery in biological networks
In this study, critical aspects of network motif discovery, design principles of background algorithms, and their functionality have been reviewed with their strengths and limitations. The performances of state-of-art algorithms are discussed in terms of runtime efficiency, scalability, and space requirement. The future scope, research direction, and challenges of the existing algorithms are presented at the end of the study. (Source: IET Systems Biology)
Source: IET Systems Biology - July 28, 2020 Category: Biology Source Type: research

eBreCaP: extreme learning-based model for breast cancer survival prediction
In this study, extreme learning machine (ELM) based model for breast cancer survival prediction named eBreCaP is proposed. It integrates the genomic (gene expression, copy number alteration, DNA methylation, protein expression) and pathological image datasets; and trains them using an ensemble of ELM with the six best-chosen models suitable to be applied on integrated data. eBreCaP has been evaluated on nine performance parameters, namely sensitivity, specificity, precision, accuracy, Matthews correlation coefficient, area under curve, area under precision–recall, hazard ratio, and concordance Index. eBreCaP has achi...
Source: IET Systems Biology - May 15, 2020 Category: Biology Source Type: research

Various skin impedance models based on physiological stratification
Transdermal drug delivery is a non-invasive method of drug administration. However, to achieve this, the drug has to pass through the complicated structure of the skin. The complex structure of skin can be modelled by an electrical equivalent circuit to calculate its impedance. In this work, the transfer function of three electrical models of the human skin (Montague, Tregear and Lykken Model) based on physiological stratification are analysed. Sensitivity analysis of these models is carried out to consider the extent to which changes in system parameters (different types of R and C as described by different models) affect...
Source: IET Systems Biology - May 15, 2020 Category: Biology Source Type: research

Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus
This study elaborates on the design of artificial pancreas using model predictive control algorithm for a comprehensive physiological model such as the Sorensen model, which regulates the blood glucose and can have a longer control time in normal glycaemic region. The main objective of the proposed algorithm is to eliminate the risk of hyper and hypoglycaemia and have a precise infusion of hormones: insulin and glucagon. A single model predictive controller is developed to control the bihormones, insulin, and glucagon for such a development unmeasured disturbance is considered for a random time. The simulation result for t...
Source: IET Systems Biology - May 15, 2020 Category: Biology Source Type: research

Robustness of a biomolecular oscillator to pulse perturbations
Biomolecular oscillators can function robustly in the presence of environmental perturbations, which can either be static or dynamic. While the effect of different circuit parameters and mechanisms on the robustness to steady perturbations has been investigated, the scenario for dynamic perturbations is relatively unclear. To address this, the authors use a benchmark three protein oscillator design – the repressilator – and investigate its robustness to pulse perturbations, computationally as well as use analytical tools of Floquet theory. They found that the metric provided by direct computations of the time i...
Source: IET Systems Biology - May 15, 2020 Category: Biology Source Type: research

Identification of specific microRNA–messenger RNA regulation pairs in four subtypes of breast cancer
This study demonstrated that the common genes in four subtypes showed different regulation. Also, the hsa-miR-182 and decorin pair performs different functions among the four subtypes of breast cancer. The result indicated that heterogeneity of breast cancer is not only reflected in the different expression patterns among different genes, but also in the different regulatory networks of the same group of genes. (Source: IET Systems Biology)
Source: IET Systems Biology - May 15, 2020 Category: Biology Source Type: research

Application of conditional robust calibration to ordinary differential equations models in computational systems biology: a comparison of two sampling strategies
Mathematical modelling is a widely used technique for describing the temporal behaviour of biological systems. One of the most challenging topics in computational systems biology is the calibration of non-linear models; i.e. the estimation of their unknown parameters. The state-of-the-art methods in this field are the frequentist and Bayesian approaches. For both of them, the performance and accuracy of results greatly depend on the sampling technique employed. Here, the authors test a novel Bayesian procedure for parameter estimation, called conditional robust calibration (CRC), comparing two different sampling techniques...
Source: IET Systems Biology - May 15, 2020 Category: Biology Source Type: research

Coupling of cell fate selection model enhances DNA damage response and may underlie BE phenomenon
This study proposes a plausible coupling model of three-mode two-dimensional oscillators, which models the p53-mediated cell fate selection in globally coupled DSB-induced cells. The coupled model consists of ATM and Wip1 proteins as variables. The coupling mechanism is realised through ATM variable via a mean-field modelling the bystander signal in the intercellular medium. Investigation of the model reveals that the coupling generates more sensitive DNA damage response by affecting cell fate selection. Additionally, the authors search for the cause-effect relationship between coupled p53 network oscillators and bystander...
Source: IET Systems Biology - March 20, 2020 Category: Biology Source Type: research

Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification
Microarray technology plays a significant role in cancer classification, where a large number of genes and samples are simultaneously analysed. For the efficient analysis of the microarray data, there is a great demand for the development of intelligent techniques. In this article, the authors propose a novel hybrid technique employing Fisher criterion, ReliefF, and extreme learning machine (ELM) based on the principle of chaotic emperor penguin optimisation algorithm (CEPO). EPO is a recently developed metaheuristic method. In the proposed method, initially, Fisher score and ReliefF are independently used as filters for r...
Source: IET Systems Biology - March 20, 2020 Category: Biology Source Type: research

Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors
This study aimed to identify molecular biomarkers involved in inflammatory CMP development and progression using a systems biology approach. The authors analysed microarray gene expression datasets from CMP and tissues affected by risk factors including smoking, ageing factors, high body fat, clinical depression status, insulin resistance, high dietary red meat intake, chronic alcohol consumption, obesity, high-calorie diet and high-fat diet. The authors identified differentially expressed genes (DEGs) from each dataset and compared those from CMP and risk factor datasets to identify common DEGs. Gene set enrichment analys...
Source: IET Systems Biology - March 20, 2020 Category: Biology Source Type: research

Dependence of bacterial growth rate on dynamic temperature changes
Temperature is an important determinant of bacterial growth. While the dependence of bacterial growth on different temperatures has been well studied for many bacterial species, prediction of bacterial growth rate for dynamic temperature changes is relatively unclear. Here, the authors address this issue using a combination of experimental measurements of the growth, at the resolution of 5 min, of Escherichia coli and mathematical models. They measure growth curves at different temperatures and estimate model parameters to predict bacterial growth profiles subject to dynamic temperature changes. They compared these predi...
Source: IET Systems Biology - March 20, 2020 Category: Biology Source Type: research

Hypnosis regulation in propofol anaesthesia employing super-twisting sliding mode control to compensate variability dynamics
This study focuses on regulation of the hypnosis level in the presence of surgical stimulus including skin incision, surgical diathermy and laryngoscopy as well as inter-patient variability by designing super-twisting sliding mode control (STSMC). The depth of the hypnosis level is maintained to 50 on the BIS level in the maintenance phase after improving the induction phase to 60 s using the conventional sliding mode control and 30 s with STSMC. The proposed scheme also compensates the inter-patient variability dynamics including height, age and weight of the different silico patients. Moreover, the surgical stimuli d...
Source: IET Systems Biology - March 20, 2020 Category: Biology Source Type: research

Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches
ANGPTL8 is a recently identified novel hormone which regulates both glucose and lipid metabolism. The increase in ANGPTL8 during compensatory insulin resistance has been recently reported to improve glucose tolerance and a part of cytoprotective metabolic circuit. However, the exact signalling entities and dynamics involved in this process have remained elusive. Therefore, the current study was conducted with a specific aim to model the regulation of ANGPTL8 with emphasis on its role in improving glucose tolerance during insulin resistance. The main contribution of this study is the construction of a discrete model (based ...
Source: IET Systems Biology - March 20, 2020 Category: Biology Source Type: research

Ensembled machine learning framework for drug sensitivity prediction
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in developing computational approaches for drug sensitivity prediction. Cancer is a complex disease involving the heterogeneous behaviour of same tumour-type patients towards the same kind of drug therapy. Several methods have been proposed in the literature to predict drug sensitivity. However, these methods are not efficient enough to predict drug sensitivity. The present study has...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Chattering-free hybrid adaptive neuro-fuzzy inference system-particle swarm optimisation data fusion-based BG-level control
In this study, a closed-loop control scheme is proposed for the glucose–insulin regulatory system in type-1 diabetic mellitus (T1DM) patients. Some innovative hybrid glucose–insulin regulators have combined artificial intelligence such as fuzzy logic and genetic algorithm with well known Palumbo model to regulate the blood glucose (BG) level in T1DM patients. However, most of these approaches have focused on the glucose reference tracking, and the qualitative of this tracking such as chattering reduction of insulin injection has not been well-studied. Higher-order sliding mode (HoSM) controllers have been emplo...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Blood glucose concentration control for type 1 diabetic patients: a multiple-model strategy
In this study, a multiple-model strategy is evaluated as an alternative closed-loop method for subcutaneous insulin delivery in type 1 diabetes. Non-linearities of the glucose–insulin regulatory system are considered by modelling the system around five different operating points. After conducting some identification experiments in the UVA/Padova metabolic simulator (accepted simulator by the US Food and Drug Administration (FDA)), five transfer functions are obtained for these operating points. Paying attention to some physiological facts, the control objectives such as the required settling time and permissible boun...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Hypoglycaemia-free artificial pancreas project
Driving blood glycaemia from hyperglycaemia to euglycaemia as fast as possible while avoiding hypoglycaemia is a major problem for decades for type-1 diabetes and is solved in this study. A control algorithm is designed that guaranties hypoglycaemia avoidance for the first time both from the theory of positive systems point of view and from the most pragmatic clinical practice. The solution consists of a state feedback control law that computes the required hyperglycaemia correction bolus in real-time to safely steer glycaemia to the target. A rigorous proof is given that shows that the control-law respects the positivity ...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Adaptive back-stepping cancer control using Legendre polynomials
Here, a model-free controller for cancer treatment is presented. The treatment objective is to find a proper drug dosage that can reduce the population of tumour cells. Recently, some solutions have been proposed according to the control theory. In these approaches, based on the mathematical description of the number of effector cells, tumour cells, and concentration of the interleukin-2 (IL-2), a non-linear controller is designed. Here, based on the back-stepping design procedure and function approximation property of Legendre polynomials, a novel controller for MIMO cancer immunotherapy is presented. In fact, Legendre po...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach
In this study, a hybrid model has been designed by using stacked generalisation ensemble technique for prediction of linear B-cell epitopes. The goal of using stacked generalisation ensemble approach is to refine predictions of base classifiers and to get rid of the worse predictions. In this study, six machine learning models are fused to predict variable length epitopes (6–49 mers). The proposed ensemble model achieves 76.6% accuracy and average accuracy of repeated 10-fold cross-validation is 73.14%. The trained ensemble model has been tested on the benchmark dataset and compared with existing sequential B-cell ep...
Source: IET Systems Biology - January 17, 2020 Category: Biology Source Type: research

Bifurcation analysis of bistable and oscillatory dynamics in biological networks using the root-locus method
This study demonstrates the applicability of the root-locus-based bifurcation analysis method for studying the complex dynamics of such models. The effectiveness of the bifurcation analysis in determining the exact parameter regions in each of which the system shows a certain dynamical behaviour, such as bistability, oscillation, and asymptotically equilibrium dynamics is shown by considering two mostly studied gene regulatory networks, namely Gardner's genetic toggle switch and p53 gene network possessing two-phase (mono-stable/oscillation) dynamics. (Source: IET Systems Biology)
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Modelling and simulation of chlorophyll fluorescence from PSII of a plant leaf as affected by both illumination light intensities and temperatures
The emission of chlorophyll fluorescence (ChlF) from photosystem II (PSII) of plant leaves the couple with photoelectron transduction cascades in photosynthetic reactions and can be used to probe photosynthetic efficiency and plant physiology. Because of population increase, food shortages, and global warming, it is becoming more and more urgent to enhance plant photosynthesis efficiency by controlling plant growth rate. An effective model structure is essential for plant control strategy development. However, there is a lack of reporting on modelling and simulation of PSII activities under the interaction of both illumina...
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Competitive analysis for stochastic influenza model with constant vaccination strategy
This manuscript discusses a competitive analysis of stochastic influenza model with constant vaccination strategy. The stochastic influenza model is comparatively more pragmatic versus the deterministic influenza model. The effect of influenza generation number holds in the stochastic model. If the value of this number is less than one, this situation will help us to control the disease in a population. A greater than one value of this threshold number shows the persistence of disease to become endemic. The proposed structure for the stochastic influenza model as stochastic non-standard finite difference scheme conserve al...
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Competitive numerical analysis for stochastic HIV/AIDS epidemic model in a two-sex population
This study is an attempt to explain a reliable numerical analysis of a stochastic HIV/AIDS model in a two-sex population considering counselling and antiretroviral therapy (ART). The authors are comparing the solutions of the stochastic and deterministic HIV/AIDS epidemic model. Here, an endeavour has been made to explain the stochastic HIV/AIDS epidemic model is comparatively more pragmatic in contrast with the deterministic HIV/AIDS epidemic model. The effect of threshold number H* holds on the stochastic HIV/AIDS epidemic model. If H*  1 explains the persistence of disease in the two-sex human population. ...
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Fuzzy cognitive map based approach for determining the risk of ischemic stroke
In this study, the soft computing method known as fuzzy cognitive mapping was proposed for diagnosis of the risk of ischemic stroke. Non-linear Hebbian learning method was used for fuzzy cognitive maps training. In the proposed method, the risk rate for each person was determined based on the opinions of the neurologists. The accuracy of the proposed model was tested using 10-fold cross-validation, for 110 real cases, and the results were compared with those of support vector machine and K-nearest neighbours. The proposed system showed a superior performance with a total accuracy of (93.6 ± 4.5)%. The ...
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Identifying genuine protein–protein interactions within communities of gene co-expression networks using a deconvolution method
Direct relationships between biological molecules connected in a gene co-expression network tend to reflect real biological activities such as gene regulation, protein–protein interactions (PPIs), and metabolisation. As correlation-based networks contain numerous indirect connections, those direct relationships are always ‘hidden’ in them. Compared with the global network, network communities imply more biological significance on predicting protein function, detecting protein complexes and studying network evolution. Therefore, identifying direct relationships in communities is a pervasive and important t...
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Analysis for fractional-order predator–prey model with uncertainty
Here, the authors analyse the fractional-order predator–prey model with uncertainty, due to the vast applications in various ecological systems. The most of the ecological model do not have exact analytic solution, so they proposed a numerical technique for an approximate solution. In the proposed method, they have implemented the higher order term into the fractional Euler method to enhance the precise solution. Further, the present attempt is aimed to discuss the solutions of the FPPM with uncertainty (fuzzy) initial conditions. The initial conditions of the predator–prey model were taken as fuzzy initial con...
Source: IET Systems Biology - November 29, 2019 Category: Biology Source Type: research

Drug repositioning via matrix completion with multi-view side information
In the process of drug discovery and disease treatment, drug repositioning is broadly studied to identify biological targets for existing drugs. Many methods have been proposed for drug-target interaction prediction by taking into account different kinds of data sources. However, most of the existing methods only use one side information for drugs or targets to predict new targets for drugs. Some recent works have improved the prediction accuracy by jointly considering multiple representations of drugs and targets. In this work, the authors propose a drug-target prediction approach by matrix completion with multi-view side...
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

Diagnosis of attention deficit hyperactivity disorder using non-linear analysis of the EEG signal
In this study, a new approach is proposed based on the combination of some non-linear features to distinguish ADHD from normal children. Lyapunov exponent, fractal dimension, correlation dimension and sample, fuzzy and approximate entropies are the non-linear extracted features. For computing, the chaotic time series of obtained EEG in the brain frontal lobe (FP1, FP2, F3, F4, and Fz) need to be analysed. Experiments on a set of EEG signal obtained from 50 ADHD and 26 normal cases yielded a sensitivity, specificity, and accuracy of 98, 92.31, and 96.05%, respectively. The obtained accuracy provides a significant improvemen...
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

Oscillation induced by Hopf bifurcation in the p53–Mdm2 feedback module
This study develops an integrated model of the p53-Mdm2 interaction composed of five basic components and time delay in the DNA damage response based on the existing research work. Some critical factors, including time delay, system parameters, and their interactions in the p53-Mdm2 system are investigated to examine their effects on the oscillatory behaviour induced by Hopf bifurcation. It is shown that the positive feedback formed between p53 and the activity of Mdm2 in the cytoplasm can cause a slight decrease in the amplitude of the p53 oscillation. The length of the time delay plays an important role in determining th...
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

Classification of drug molecules for oxidative stress signalling pathway
In humans, oxidative stress is involved in the development of diabetes, cancer, hypertension, Alzheimers' disease, and heart failure. One of the mechanisms in the cellular defence against oxidative stress is the activation of the Nrf2-antioxidant response element (ARE) signalling pathway. Computation of activity, efficacy, and potency score of ARE signalling pathway and to propose a multi-level prediction scheme for the same is the main aim of the study as it contributes in a big amount to the improvement of oxidative stress in humans. Applying the process of knowledge discovery from data, required knowledge is gathered an...
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

Biclustering-based association rule mining approach for predicting cancer-associated protein interactions
This study shows the prediction power of association rule mining algorithm over the traditional classifier model without choosing a negative data set. The time complexity of the biclustering-based association rule mining is also analysed and compared to traditional association rule mining. The authors are able to discover 38 new PPIs which are not present in the cancer database. The biological relevance of these newly predicted interactions is analysed by published literature. Recognition of such interactions may accelerate a way of developing new drugs to prevent different cancer-related diseases. (Source: IET Systems Biology)
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

Down-regulation and clinical significance of miR-7-2-3p in papillary thyroid carcinoma with multiple detecting methods
Altered miRNA expression participates in the biological progress of thyroid carcinoma and functions as a diagnostic marker or therapeutic agent. However, the role of miR-7-2-3p is currently unclear. The authors' study was the first investigation of miR-7-2-3p expression level and diagnostic ability in several public databases. Potential target genes were obtained from DIANA Tools, and function enrichment analysis was then performed. Furthermore, the authors examined expression levels of potential targets in the Human Protein Atlas (HPA) and the Cancer Genome Atlas (TCGA). Finally, the potential transcription factors (TFs) ...
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

Disjoint motif discovery in biological network using pattern join method
In this study, an efficient pattern-join based algorithm is proposed to discover network motif in biological networks. The performance of the proposed algorithm is evaluated on the transcription regulatory network of Escherichia coli and the protein interaction network of Saccharomyces cerevisiae. The running time of the proposed algorithm outperforms most of the existing algorithms to discover large motifs. (Source: IET Systems Biology)
Source: IET Systems Biology - October 23, 2019 Category: Biology Source Type: research

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