-
Experimental evidence for constraints in amplitude-timescale co-variation of a biomolecular pulse generating circuit design IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-19 Abhilash Patel; Shaunak Sen
Understanding constraints on the functional properties of biomolecular circuit dynamics, such as the possible variations of amplitude and timescale of a pulse, is an important part of biomolecular circuit design. While the amplitude-timescale co-variations of the pulse in an incoherent feedforward loop have been investigated computationally using mathematical models, experimental support for any such
-
Sliding mode control for a fractional-order non-linear glucose-insulin system IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Muhammad Waleed Khan; Muhammad Abid; Abdul Qayyum Khan; Ghulam Mustafa; Muzamil Ali; Asifullah Khan
By providing the generalisation of integration and differentiation, and incorporating the memory and hereditary effects, fractional-order modelling has gotten significant attention in the past few years. One of the extensively studied and utilised models to describe the glucose–insulin system of a human body is Bergman's minimal model. This non-linear model comprises of integer-order differential equations
-
Estimation of skin impedance models with experimental data and a proposed model for human skin impedance IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Dhruba Jyoti Bora; Rajdeep Dasgupta
The skin is a complex biological tissue whose impedance varies with frequency. The properties and structure of skin changes with the location on the body, age, geographical location and other factors. Considering these factors, skin impedance analysis is a sophisticated data analysis. However, despite all these variations, various researchers have always worked to develop an equivalent electrical model
-
Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Cifha Crecil Dias; Surekha Kamath; Sudha Vidyasagar
The complete automated control and delivery of insulin and glucagon in type 1 diabetes is the developing technology for artificial pancreas. This improves the quality of life of a diabetic patient with the precise infusion. The amount of infusion of these hormones is controlled using a control algorithm, which has the prediction property. The control algorithm model predictive control (MPC) predicts
-
Integrated expression analysis revealed RUNX2 upregulation in lung squamous cell carcinoma tissues IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Da-Ping Yang; Hui-Ping Lu; Gang Chen; Jie Yang; Li Gao; Jian-Hua Song; Shang-Wei Chen; Jun-Xian Mo; Jin-Liang Kong; Zhong-Qing Tang; Chang-Bo Li; Hua-Fu Zhou; Lin-Jie Yang
This study aimed to investigate the clinicopathological significance and prospective molecular mechanism of RUNX family transcription factor 2 (RUNX2) in lung squamous cell carcinoma (LUSC). The authors used immunohistochemistry (IHC), RNA-seq, and microarray data from multi-platforms to conduct a comprehensive analysis of the clinicopathological significance and molecular mechanism of RUNX2 in the
-
Pseudo-spectral method for controlling the drug dosage in cancer IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Mostafa Nazari; Morteza Nazari; Mohammad Hadi Noori Skandari
A mixed chemotherapy–immunotherapy treatment protocol is developed for cancer treatment. Chemotherapy pushes the trajectory of the system towards the desired equilibrium point, and then immunotherapy alters the dynamics of the system by affecting the parameters of the system. A co-existing cancerous equilibrium point is considered as the desired equilibrium point instead of the tumour-free equilibrium
-
Formal reasoning about synthetic biology using higher-order-logic theorem proving IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Sa'ed Abed; Adnan Rashid; Osman Hasan
Synthetic biology is an interdisciplinary field that uses well-established engineering principles for performing the analysis of the biological systems, such as biological circuits, pathways, controllers and enzymes. Conventionally, the analysis of these biological systems is performed using paper-and-pencil proofs and computer simulation methods. However, these methods cannot ensure accurate results
-
Combinatorial dynamics of protein synthesis time delay and negative feedback loop in NF-κB signalling pathway IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Fang Yan; Li Liu; Qingyun Wang
The transcription factor NF- κ B links immune response and inflammatory reaction and its different oscillation patterns determine different cell fates. In this study, a mathematical model with I κ B α protein synthesis time delay is developed based on the experimental evidences. The results show that time delay has the ability to drive oscillation of NF- κ B via Hopf bifurcation. Meanwhile, the amplitude
-
Identification of robust genes in transcriptional regulatory network of Mycobacterium tuberculosis IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Prithvi Singh; Mohd Amir; Upasana Chaudhary; Fozail Ahmad; Sachin Bhatt; Shweta Sankhwar; Ravins Dohare
About 30% of the world population is infected with Mycobacterium tuberculosis (MTB). It is well known that the gene expression in MTB is highly variable, thus screening of traditional single-gene in MTB has been incapable to meet the desires of clinical diagnosis. In this report, the authors systemically analysed the transcription regulatory network (TRN) in MTB H37Rv. The complex interplay of these
-
Bifurcation and oscillatory dynamics of delayed CDK1-APC feedback loop IET Syst. Biol. (IF 1.0) Pub Date : 2020-10-13 Shenshuang Zhou; Wei Zhang; Yuan Zhang; Xuan Ni; Zhouhong Li
Extensive experimental evidence has been demonstrated that the dynamics of CDK1-APC feedback loop play crucial roles in regulating cell cycle processes, but the dynamical mechanisms underlying the regulation of this loop are still not completely understood. Here, the authors systematically investigated the stability and bifurcation criteria for a delayed CDK1-APC feedback loop. They showed that the
-
Review of tools and algorithms for network motif discovery in biological networks. IET Syst. Biol. (IF 1.0) Pub Date : 2020-07-27 Sabyasachi Patra,Anjali Mohapatra
Network motifs are recurrent and over-represented patterns having biological relevance. This is one of the important local properties of biological networks. Network motif discovery finds important applications in many areas such as functional analysis of biological components, the validity of network composition, classification of networks, disease discovery, identification of unique subunits etc
-
Modelling and analysing biological oscillations in quorum sensing networks. IET Syst. Biol. (IF 1.0) Pub Date : 2020-07-27 Menghan Chen,Haihong Liu,Fang Yan
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
-
Novel algebraic meal disturbance estimation based adaptive robust control design for blood glucose regulation in type 1 diabetes patients. IET Syst. Biol. (IF 1.0) Pub Date : 2020-07-27 Nasim Ullah,Al-Sharef Muhammad
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
-
Efficient prediction of drug-drug interaction using deep learning models. IET Syst. Biol. (IF 1.0) Pub Date : 2020-07-27 Prashant Kumar Shukla,Piyush Kumar Shukla,Poonam Sharma,Paresh Rawat,Jashwant Samar,Rahul Moriwal,Manjit Kaur
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
-
eBreCaP: extreme learning-based model for breast cancer survival prediction. IET Syst. Biol. (IF 1.0) Pub Date : 2020-06-01 Arwinder Dhillon,Ashima Singh
Breast cancer is the second leading cause of death in the world. Breast cancer research is focused towards its early prediction, diagnosis, and prognosis. Breast cancer can be predicted on omics profiles, clinical tests, and pathological images. The omics profiles comprise of genomic, proteomic, and transcriptomic profiles that are available as high-dimensional datasets. Survival prediction is carried
-
Various skin impedance models based on physiological stratification. IET Syst. Biol. (IF 1.0) Pub Date : 2020-06-01 Dhruba Jyoti Bora,Rajdeep Dasgupta
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
-
Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus. IET Syst. Biol. (IF 1.0) Pub Date : 2020-06-01 Cifha Crecil Dias,Surekha Kamath,Sudha Vidyasagar
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:
-
Robustness of a biomolecular oscillator to pulse perturbations. IET Syst. Biol. (IF 1.0) Pub Date : 2020-06-01 Soumyadip Banerjee,Shaunak Sen
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
-
Identification of specific microRNA-messenger RNA regulation pairs in four subtypes of breast cancer. IET Syst. Biol. (IF 1.0) Pub Date : 2020-06-01 Ling Guo,Aihua Zhang,Jie Xiong
Four subtypes of breast cancer, luminal A, luminal B, basal-like, human epidermal growth factor receptor-enriched, have been identified based on gene expression profiles of human tumours. The goal of this study is to find whether the same groups' genes would exhibit different networks among the four subtypes. Differential expressed genes between each of the four subtypes and the normal samples were
-
Application of conditional robust calibration to ordinary differential equations models in computational systems biology: a comparison of two sampling strategies. IET Syst. Biol. (IF 1.0) Pub Date : 2020-06-01 Fortunato Bianconi,Chiara Antonini,Lorenzo Tomassoni,Paolo Valigi
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
-
Coupling of cell fate selection model enhances DNA damage response and may underlie BE phenomenon. IET Syst. Biol. (IF 1.0) Pub Date : 2020-04-01 Gökhan Demirkıran,Güleser Kalaycı Demir,Cüneyt Güzeliş
Double-strand break-induced (DSB) cells send signal that induces DSBs in neighbour cells, resulting in the interaction among cells sharing the same medium. Since p53 network gives oscillatory response to DSBs, such interaction among cells could be modelled as an excitatory coupling of p53 network oscillators. This study proposes a plausible coupling model of three-mode two-dimensional oscillators,
-
Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification. IET Syst. Biol. (IF 1.0) Pub Date : 2020-04-01 Santos Kumar Baliarsingh,Swati Vipsita
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
-
Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors. IET Syst. Biol. (IF 1.0) Pub Date : 2020-04-01 Md Nasim Haidar,M Babul Islam,Utpala Nanda Chowdhury,Md Rezanur Rahman,Fazlul Huq,Julian M W Quinn,Mohammad Ali Moni
Cardiomyopathy (CMP) is a group of myocardial diseases that progressively impair cardiac function. The mechanisms underlying CMP development are poorly understood, but lifestyle factors are clearly implicated as 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
-
Dependence of bacterial growth rate on dynamic temperature changes. IET Syst. Biol. (IF 1.0) Pub Date : 2020-04-01 Abhishek Dey,Venkat Bokka,Shaunak Sen
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
-
Hypnosis regulation in propofol anaesthesia employing super-twisting sliding mode control to compensate variability dynamics. IET Syst. Biol. (IF 1.0) Pub Date : 2020-04-01 Muhammad Ilyas,Jamshed Iqbal,Sayyar Ahmad,Ali Arshad Uppal,Waqas Ahmad Imtiaz,Raja Ali Riaz
Regulation of hypnosis level on bi-spectral index monitor (BIS) during a surgical procedure in propofol anaesthesia administration is a challenging task for an anaesthesiologist in multi-tasking environment of the operation theater. Automation in anaesthesia has the potential to solve issues arising from manual administration. Automation in anaesthesia is based on developing the three-compartmental
-
Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches. IET Syst. Biol. (IF 1.0) Pub Date : 2020-04-01 Amnah Siddiqa,Jamil Ahmad,Amjad Ali,Sharifullah Khan
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
-
Ensembled machine learning framework for drug sensitivity prediction. IET Syst. Biol. (IF 1.0) Pub Date : 2020-02-01 Aman Sharma,Rinkle Rani
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
-
Chattering-free hybrid adaptive neuro-fuzzy inference system-particle swarm optimisation data fusion-based BG-level control. IET Syst. Biol. (IF 1.0) Pub Date : 2020-02-01 Ali Karsaz
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
-
Blood glucose concentration control for type 1 diabetic patients: a multiple-model strategy. IET Syst. Biol. (IF 1.0) Pub Date : 2020-02-01 Yazdan Batmani,Shadi Khodakaramzadeh
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
-
Hypoglycaemia-free artificial pancreas project. IET Syst. Biol. (IF 1.0) Pub Date : 2020-02-01 Nicolas Magdelaine,Pablo S Rivadeneira,Lucy Chaillous,Anne-Laure Fournier-Guilloux,Michel Krempf,Taghreed MohammadRidha,Mourad Ait-Ahmed,Claude H Moog
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
-
Adaptive back-stepping cancer control using Legendre polynomials. IET Syst. Biol. (IF 1.0) Pub Date : 2020-02-01 Saeed Khorashadizadeh,Ali Akbarzadeh Kalat
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
-
Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach. IET Syst. Biol. (IF 1.0) Pub Date : 2020-02-01 Divya Khanna,Prashant Singh Rana
The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B-cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to develop a reliable model with significant improvement in prediction models. In this study, a hybrid model has been designed by using stacked generalisation
-
Bifurcation analysis of bistable and oscillatory dynamics in biological networks using the root-locus method. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Neslihan Avcu,Cüneyt Güzeliş
Most of the biological systems including gene regulatory networks can be described well by ordinary differential equation models with rational non-linearities. These models are derived either based on the reaction kinetics or by curve fitting to experimental data. This study demonstrates the applicability of the root-locus-based bifurcation analysis method for studying the complex dynamics of such
-
Modelling and simulation of chlorophyll fluorescence from PSII of a plant leaf as affected by both illumination light intensities and temperatures. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Lijiang Fu,Qian Xia,Jinglu Tan,Hao Wu,Ya Guo
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
-
Competitive analysis for stochastic influenza model with constant vaccination strategy. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Dumitru Baleanu,Ali Raza,Muhammad Rafiq,Muhammad Shoaib Arif,Muhammad Asghar Ali
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
-
Competitive numerical analysis for stochastic HIV/AIDS epidemic model in a two-sex population. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Ali Raza,Muhammad Rafiq,Dumitru Baleanu,Muhammad Shoaib Arif,Muhammad Naveed,Kaleem Ashraf
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
-
Fuzzy cognitive map based approach for determining the risk of ischemic stroke. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Mahsa Khodadadi,Heidarali Shayanfar,Keivan Maghooli,Amir Hooshang Mazinan
Stroke is the third major cause of mortality in the world. The diagnosis of stroke is a very complex issue considering controllable and uncontrollable factors. These factors include age, sex, blood pressure, diabetes, obesity, heart disease, smoking, and so on, having a considerable influence on the diagnosis of stroke. Hence, designing an intelligent system leading to immediate and effective treatment
-
Identifying genuine protein-protein interactions within communities of gene co-expression networks using a deconvolution method. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Jin Zhang,Shan Ju
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
-
Analysis for fractional-order predator-prey model with uncertainty. IET Syst. Biol. (IF 1.0) Pub Date : 2019-11-30 Samayan Narayanamoorthy,Dumitru Baleanu,Kalidas Thangapandi,Shyam Sanjeewa Nishantha Perera
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
-
Drug repositioning via matrix completion with multi-view side information. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Yunda Hao,Menglan Cai,Limin Li
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
-
Diagnosis of attention deficit hyperactivity disorder using non-linear analysis of the EEG signal. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Yasaman Kiani Boroujeni,Ali Asghar Rastegari,Hamed Khodadadi
Attention deficit hyperactivity disorder (ADHD) is a common behavioural disorder that may be found in 5%-8% of the children. Early diagnosis of ADHD is crucial for treating the disease and reducing its harmful effects on education, employment, relationships, and life quality. On the other hand, non-linear analysis methods are widely applied in processing the electroencephalogram (EEG) signals. It has
-
Oscillation induced by Hopf bifurcation in the p53-Mdm2 feedback module. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Chunyan Gao,Jinchen Ji,Fang Yan,Haihong Liu
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
-
Classification of drug molecules for oxidative stress signalling pathway. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Nikhil Verma,Harpreet Singh,Divya Khanna,Prashant Singh Rana,Sanjay Kumar Bhadada
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
-
Biclustering-based association rule mining approach for predicting cancer-associated protein interactions. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Lopamudra Dey,Anirban Mukhopadhyay
Protein-protein interactions (PPIs) have been widely used to understand different biological processes and cellular functions associated with several diseases like cancer. Although some cancer-related protein interaction databases are available, lack of experimental data and conflicting PPI data among different available databases have slowed down the cancer research. Therefore, in this study, the
-
Down-regulation and clinical significance of miR-7-2-3p in papillary thyroid carcinoma with multiple detecting methods. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Hua-Yu Wu,Yi Wei,Shang-Ling Pan
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
-
Disjoint motif discovery in biological network using pattern join method. IET Syst. Biol. (IF 1.0) Pub Date : 2019-10-01 Sabyasachi Patra,Anjali Mohapatra
The biological network plays a key role in protein function annotation, protein superfamily classification, disease diagnosis, etc. These networks exhibit global properties like small-world property, power-law degree distribution, hierarchical modularity, robustness, etc. Along with these, the biological network also possesses some local properties like clustering and network motif. Network motifs
-
Sliding mode controller-observer pair for p53 pathway. IET Syst. Biol. (IF 1.0) Pub Date : 2019-08-01 Muhammad Rizwan Azam,Vadim I Utkin,Ali Arshad Uppal,Aamer Iqbal Bhatti
A significant loss of p53 protein, an anti-tumour agent, is observed in early cancerous cells. Induction of small molecules based drug is by far the most prominent technique to revive and maintain wild-type p53 to the desired level. 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
-
Mining conditions specific hub genes from RNA-Seq gene-expression data via biclustering and their application to drug discovery. IET Syst. Biol. (IF 1.0) Pub Date : 2019-08-01 Ankush Maind,Shital Raut
Gene-expression data is being widely used for various clinical research. It represents expression levels of thousands of genes across the various experimental conditions simultaneously. Mining conditions specific hub genes from gene-expression data is a challenging task. Conditions specific hub genes signify the functional behaviour of bicluster across the subset of conditions and can act as prognostic
-
Control strategy design for the anti-HBV mathematical model. IET Syst. Biol. (IF 1.0) Pub Date : 2019-08-01 Yi Ding,Wen-June Wang
Currently, the anti-viral therapy has been extensively utilised to reduce the viral burden and switch off certain infectious sources for hepatitis B virus (HBV) infected patients in clinical treatment. Several pieces of existing evidence have demonstrated that large-scale coverage with anti-viral therapy has obtained a certain great contribution in hygiene and disease control. In this study, an anti-HBV
-
Contribution of time delays to p53 oscillation in DNA damage response. IET Syst. Biol. (IF 1.0) Pub Date : 2019-08-01 Conghua Wang,Haihong Liu,Jin Zhou
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
-
Identification of a time-varying intracellular signalling model through data clustering and parameter selection: application to NF-[inline-formula removed]B signalling pathway induced by LPS in the presence of BFA. IET Syst. Biol. (IF 1.0) Pub Date : 2019-08-01 Dongheon Lee,Arul Jayaraman,Joseph Sang-Il Kwon
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
-
Hilbert transform-based time-series analysis of the circadian gene regulatory network. IET Syst. Biol. (IF 1.0) Pub Date : 2019-08-01 Shiju S,K Sriram
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
-
Activity assessment of small drug molecules in estrogen receptor using multilevel prediction model. IET Syst. Biol. (IF 1.0) Pub Date : 2019-06-01 Vishan Kumar Gupta,Prashant Singh Rana
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)
-
Robust multi-objective blood glucose control in Type-1 diabetic patient. IET Syst. Biol. (IF 1.0) Pub Date : 2019-06-01 Sharmistha Mandal,Ashoke Sutradhar
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
-
Cancer adjuvant chemotherapy prediction model for non-small cell lung cancer. IET Syst. Biol. (IF 1.0) Pub Date : 2019-06-01 Russul Alanni,Jingyu Hou,Hasseeb Azzawi,Yong Xiang
Non-small cell lung cancer (NSCLC) is the most popular and dangerous type of lung cancer. Adjuvant chemotherapy (ACT) is the main treatment after surgery resection to prevent the patient from cancer recurrence. However, ACT could be toxic and unhelpful in some cases. Therefore, it is highly desired in clinical applications to predict the treatment outcomes of chemotherapy. Conventional methods of predicting
-
Robust control of HIV infection by antiretroviral therapy: a super-twisting sliding mode control approach. IET Syst. Biol. (IF 1.0) Pub Date : 2019-06-01 Manas Kumar Bera,Pintu Kumar,Raj Kumar Biswas
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
-
Effective sampling trajectory optimisation for sensitivity analysis of biological systems. IET Syst. Biol. (IF 1.0) Pub Date : 2019-06-01 Zhao Z Xu,Ji Liu
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
-
Modelling and simulation of photosynthetic activities in C3 plants as affected by CO2. IET Syst. Biol. (IF 1.0) Pub Date : 2019-06-01 Sheng Wang,Hao Tang,Qian Xia,Yongnian Jiang,Jinglu Tan,Ya Guo
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
-
Control of depth of anaesthesia using fractional-order adaptive high-gain controller. IET Syst. Biol. (IF 1.0) Pub Date : 2019-02-01 Maryam Boroujerdi Alavi,Mohammad Tabatabaei
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)
-
Switching control strategy for the HIV dynamic system with some unknown parameters. IET Syst. Biol. (IF 1.0) Pub Date : 2019-02-01 Yi Ding,Wen-June Wang
In human immunodeficiency virus (HIV) infection, many factors may influence the counts of healthy cells, immune cells and viruses. Drug treatment design for the HIV dynamic system is a valuable subject to be studied. 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
Contents have been reproduced by permission of the publishers.