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
