IET Systems BiologyPub Date : 2021-02-01Epub Date: 2020-12-08DOI: 10.1049/syb2.12009
Sujay Saha, Saikat Bandopadhyay, Anupam Ghosh
{"title":"Identifying the degree of genetic interactions using Restricted Boltzmann Machine-A study on colorectal cancer.","authors":"Sujay Saha, Saikat Bandopadhyay, Anupam Ghosh","doi":"10.1049/syb2.12009","DOIUrl":"https://doi.org/10.1049/syb2.12009","url":null,"abstract":"<p><p>The phenomenon of two or more genes affecting the expression of each other in various ways in the development of a single character of an organism is known as gene interaction. Gene interaction not only applies to normal human traits but to the diseased samples as well. Thus, an analysis of gene interaction could help us to differentiate between the normal and the diseased samples or between the two/more phases any diseased samples. At the first stage of this work we have used restricted Boltzmann machine model to find such significant interactions present in normal and/or cancer samples of every gene pairs of 20 genes of colorectal cancer data set (GDS4382) along with the weight/degree of those interactions. Later on, we are looking for those interactions present in adenoma and/or carcinoma samples of the same 20 genes of colorectal cancer data set (GDS1777). The weight/degree of those interactions represents how strong/weak an interaction is. At the end we will create a gene regulatory network with the help of those interactions, where the regulatory genes are identified by using Naïve Bayes Classifier. Experimental results are validated biologically by comparing the interactions with NCBI databases.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1049/syb2.12009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25372554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhi-Guang Huang, Yu Sun, Gang Chen, Yi-Wu Dang, Hui-Ping Lu, Juan He, Ji-Wen Cheng, Mao-Lin He, Sheng-Hua Li
{"title":"MiRNA-145-5p expression and prospective molecular mechanisms in the metastasis of prostate cancer.","authors":"Zhi-Guang Huang, Yu Sun, Gang Chen, Yi-Wu Dang, Hui-Ping Lu, Juan He, Ji-Wen Cheng, Mao-Lin He, Sheng-Hua Li","doi":"10.1049/syb2.12011","DOIUrl":"https://doi.org/10.1049/syb2.12011","url":null,"abstract":"<p><p>The clinicopathological implication and prospective molecular mechanisms of miRNA-145-5p in the metastasis of prostate cancer (PCa) stand unclear. Herein, it is found that miRNA-145-5p expression was remarkably reduced in 131 cases of metastatic PCa than 1371 cases of localised ones, as the standardised mean differences (SMD) was -1.26 and the area under the curve (AUC) was 0.86, based on miRNA-chip and miRNA-sequencing datasets. The potential targets of miRNA-145-5p in metastatic PCa (n = 414) was achieved from the intersection of miRNA-145-5p transfected metastatic PCa cell line data, differential expression of metastatic PCa upregulated genes and online prediction databases. TOP2A was screened as one of the target hub genes by PPI network analysis, which was adversely related to miRNA-145-5p expression in both metastatic PCa (r = -0.504) and primary PCa (r = -0.281). Gene-chip and RNA-sequencing datasets, as well as IHC performed on clinical PCa samples, showed consistent upregulated expression of TOP2A mRNA and protein in PCa compared with non-PCa. The expression of TOP2A mRNA was also significantly higher in metastatic than localised PCa with the SMD being 1.72 and the AUC of sROC being 0.91. In summary, miRNA-145-5p may participate in PCa metastasis by binding TOP2A and be useful as a biomarker for the detection of metastatic PCa.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675798/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25321330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification and analysis of circRNA–miRNA–mRNA regulatory network in hepatocellular carcinoma","authors":"Daxiang Zhou, Ling Dong, Lishan Yang, Qiang Ma, Feng Liu, Yanjie Li, Shu Xiong","doi":"10.1049/iet-syb.2020.0061","DOIUrl":"10.1049/iet-syb.2020.0061","url":null,"abstract":"<div>\u0000 <p>This study was to identify important circRNA–miRNA–mRNA (ceRNAs) regulatory mechanisms in hepatocellular carcinoma (HCC). The circRNA dataset GSE97332 and miRNA dataset GSE57555 were used for analyses. Functional enrichment analysis for miRNA and target gene was conducted using cluster Profiler. Survival analysis was conducted through R package Survival. The ceRNAs and drug–gene interaction networks were constructed. The ceRNAs network contained five miRNAs including hsa-miR-25-3p, hsa-miR-3692-5p, hsa-miR-4270, hsa-miR-331-3p, and hsa-miR-125a-3p. Among the network, hsa-miR-25-3p targeted the most genes, hsa-miR-3692-5p and hsa-miR-4270 were targeted by more circRNAs than other miRNAs, hsa-circ-0034326 and hsa-circ-0011950 interacted with three miRNAs. Furthermore, target genes, including <i>NRAS</i>, <i>ITGA5</i>, <i>SLC7A1</i>, <i>SEC14L2</i>, <i>SLC12A5</i>, and <i>SMAD2</i> were obtained in drug–gene interaction network. Survival analysis showed <i>NRAS</i>, <i>ITGA5</i>, <i>SLC7A1</i>, <i>SEC14L2</i>, <i>SLC12A5</i>, and <i>SMAD2</i> were significantly associated with prognosis of HCC. <i>NRAS</i>, <i>ITGA5</i>, and <i>SMAD2</i> were significantly enriched in proteoglycans in cancer. Moreover, hsa-circ-0034326 and hsa-circ-0011950 might function as ceRNAs to play key roles in HCC. Furthermore, miR-25-3p, miR-3692-5p, and miR-4270 might be significant for HCC development. <i>NRAS</i>, <i>ITGA5</i>, <i>SEC14L2</i>, <i>SLC12A5</i>, and <i>SMAD2</i> might be prognostic factors for HCC patients via proteoglycans in cancer pathway. Taken together, the findings will provide novel insight into pathogenesis, selection of therapeutic targets and prognostic factors for HCC.</p></div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687197/pdf/SYB2-14-391.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38781494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Petri Net modelling approach for analysing the behaviour of Wnt/ -catenin and Wnt/ Ca2+ signalling pathways in arrhythmogenic right ventricular cardiomyopathy","authors":"Nazia Azim, Jamil Ahmad, Nadeem Iqbal, Amnah Siddiqa, Abdul Majid, Javaria Ashraf, Fazal Jalil","doi":"10.1049/iet-syb.2020.0038","DOIUrl":"10.1049/iet-syb.2020.0038","url":null,"abstract":"<div>\u0000 <p>Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that may result in arrhythmia, heart failure and sudden death. The hallmark pathological findings are progressive myocyte loss and fibro fatty replacement, with a predilection for the right ventricle. This study focuses on the adipose tissue formation in cardiomyocyte by considering the signal transduction pathways including <i>Wnt/</i> <i>-catenin</i> and <i>Wnt/Ca<sup>2+</sup></i> regulation system. These pathways are modelled and analysed using stochastic petri nets (SPN) in order to increase our comprehension of ARVC and in turn its treatment regimen. The <i>Wnt/</i> <i>-catenin</i> model predicts that the dysregulation or absence of <i>Wnt</i> signalling, inhibition of dishevelled and elevation of glycogen synthase kinase 3 along with casein kinase I are key cytotoxic events resulting in apoptosis. Moreover, the <i>Wnt/Ca<sup>2+</sup></i> SPN model demonstrates that the <i>Bcl2</i> gene inhibited by <i>c-Jun N-terminal kinase</i> protein in the event of endoplasmic reticulum stress due to action potential and increased amount of intracellular Ca<sup>2<i>+</i></sup> which recovers the Ca<sup>2<i>+</i></sup> homeostasis by phospholipase C, this event positively regulates the <i>Bcl2</i> to suppress the mitochondrial apoptosis which causes ARVC.</p>\u0000 </div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687399/pdf/SYB2-14-350.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38783048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal minimum variance-entropy control of tumour growth processes based on the Fokker–Planck equation","authors":"Maliheh Sargolzaei, Gholamreza Latif-Shabgahi, Mahdi Afshar","doi":"10.1049/iet-syb.2020.0055","DOIUrl":"10.1049/iet-syb.2020.0055","url":null,"abstract":"<div>\u0000 <p>The authors demonstrated an optimal stochastic control algorithm to obtain desirable cancer treatment based on the Gompertz model. Two external forces as two time-dependent functions are presented to manipulate the growth and death rates in the drift term of the Gompertz model. These input signals represent the effect of external treatment agents to decrease tumour growth rate and increase tumour death rate, respectively. Entropy and variance of cancerous cells are simultaneously controlled based on the Gompertz model. They have introduced a constrained optimisation problem whose cost function is the variance of a cancerous cells population. The defined entropy is based on the probability density function of affected cells was used as a constraint for the cost function. Analysing growth and death rates of cancerous cells, it is found that the logarithmic control signal reduces the growth rate, while the hyperbolic tangent–like control function increases the death rate of tumour growth. The two optimal control signals were calculated by converting the constrained optimisation problem into an unconstrained optimisation problem and by using the real–coded genetic algorithm. Mathematical justifications are implemented to elucidate the existence and uniqueness of the solution for the optimal control problem.</p>\u0000 </div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687311/pdf/SYB2-14-368.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38783049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-bit Boolean model for chemotactic drift of Escherichia coli","authors":"Anuj Deshpande, Sibendu Samanta, Sutharsan Govindarajan, Ritwik Kumar Layek","doi":"10.1049/iet-syb.2020.0060","DOIUrl":"10.1049/iet-syb.2020.0060","url":null,"abstract":"<div>\u0000 <p>Dynamic biological systems can be modelled to an equivalent modular structure using Boolean networks (BNs) due to their simple construction and relative ease of integration. The chemotaxis network of the bacterium <i>Escherichia coli</i> (<i>E. coli</i> ) is one of the most investigated biological systems. In this study, the authors developed a multi-bit Boolean approach to model the drifting behaviour of the <i>E. coli</i> chemotaxis system. Their approach, which is slightly different than the conventional BNs, is designed to provide finer resolution to mimic high-level functional behaviour. Using this approach, they simulated the transient and steady-state responses of the chemoreceptor sensory module. Furthermore, they estimated the drift velocity under conditions of the exponential nutrient gradient. Their predictions on chemotactic drifting are in good agreement with the experimental measurements under similar input conditions. Taken together, by simulating chemotactic drifting, they propose that multi-bit Boolean methodology can be used for modelling complex biological networks. Application of the method towards designing bio-inspired systems such as nano-bots is discussed.</p>\u0000 </div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687284/pdf/SYB2-14-343.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38783047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Efficient heart disease prediction-based on optimal feature selection using DFCSS and classification by improved Elman-SFO","authors":"Jaishri Wankhede, Magesh Kumar, Palaniappan Sambandam","doi":"10.1049/iet-syb.2020.0041","DOIUrl":"10.1049/iet-syb.2020.0041","url":null,"abstract":"<div>\u0000 <p>Prediction of cardiovascular disease (CVD) is a critical challenge in the area of clinical data analysis. In this study, an efficient heart disease prediction is developed based on optimal feature selection. Initially, the data pre-processing process is performed using data cleaning, data transformation, missing values imputation, and data normalisation. Then the decision function-based chaotic salp swarm (DFCSS) algorithm is used to select the optimal features in the feature selection process. Then the chosen attributes are given to the improved Elman neural network (IENN) for data classification. Here, the sailfish optimisation (SFO) algorithm is used to compute the optimal weight value of IENN. The combination of DFCSS–IENN-based SFO (IESFO) algorithm effectively predicts heart disease. The proposed (DFCSS–IESFO) approach is implemented in the Python environment using two different datasets such as the University of California Irvine (UCI) Cleveland heart disease dataset and CVD dataset. The simulation results proved that the proposed scheme achieved a high-classification accuracy of 98.7% for the CVD dataset and 98% for the UCI dataset compared to other classifiers, such as support vector machine, K-nearest neighbour, Elman neural network, Gaussian Naive Bayes, logistic regression, random forest, and decision tree.</p>\u0000 </div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687167/pdf/SYB2-14-380.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38783050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"TriRNSC: triclustering of gene expression microarray data using restricted neighbourhood search","authors":"Bhawani Sankar Biswal, Sabyasachi Patra, Anjali Mohapatra, Swati Vipsita","doi":"10.1049/iet-syb.2020.0024","DOIUrl":"10.1049/iet-syb.2020.0024","url":null,"abstract":"<div>\u0000 <p>Computational analysis of microarray data is crucial for understanding the gene behaviours and deriving meaningful results. Clustering and biclustering of gene expression microarray data in the unsupervised domain are extremely important as their outcomes directly dominate healthcare research in many aspects. However, these approaches fail when the time factor is added as the third dimension to the microarray datasets. This three-dimensional data set can be analysed using triclustering that discovers similar gene sets that pursue identical behaviour under a subset of conditions at a specific time point. A novel triclustering algorithm (TriRNSC) is proposed in this manuscript to discover meaningful triclusters in gene expression profiles. TriRNSC is based on restricted neighbourhood search clustering (RNSC), a popular graph-based clustering approach considering the genes, the experimental conditions and the time points at an instance. The performance of the proposed algorithm is evaluated in terms of volume and some performance measures. Gene Ontology and KEGG pathway analysis are used to validate the TriRNSC results biologically. The efficiency of TriRNSC indicates its capability and reliability and also demonstrates its usability over other state-of-art schemes. The proposed framework initiates the application of the RNSC algorithm in the triclustering of gene expression profiles.</p>\u0000 </div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687346/pdf/SYB2-14-323.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38783045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Waqar Alam, Qudrat Khan, Raja Ali Riaz, Rini Akmeliawati
{"title":"Arbitrary-order sliding mode-based robust control algorithm for the developing artificial pancreas mechanism","authors":"Waqar Alam, Qudrat Khan, Raja Ali Riaz, Rini Akmeliawati","doi":"10.1049/iet-syb.2018.5075","DOIUrl":"10.1049/iet-syb.2018.5075","url":null,"abstract":"<div>\u0000 <p>In Diabetes Mellitus, the pancreas remains incapable of insulin administration that leads to hyperglycaemia, an escalated glycaemic concentration, which may stimulate many complications. To circumvent this situation, a closed-loop control strategy is much needed for the exogenous insulin infusion in diabetic patients. This closed-loop structure is often termed as an artificial pancreas that is generally established by the employment of different feedback control strategies. In this work, the authors have proposed an arbitrary-order sliding mode control approach for development of the said mechanism. The term, arbitrary, is exercised in the sense of its applicability to any <i>n</i> -order controllable canonical system. The proposed control algorithm affirms the finite-time effective stabilisation of the glucose–insulin regulatory system, at the desired level, with the alleviation of sharp fluctuations. The novelty of this work lies in the sliding manifold that incorporates indirect non-linear terms. In addition, the necessary discontinuous terms are filtered-out once before its employment to the plant, i.e. diabetic patient. The robustness, in the presence of external disturbances, i.e. meal intake is confirmed via rigorous mathematical stability analysis. In addition, the effectiveness of the proposed control strategy is ascertained by comparing the results with the standard literature.</p>\u0000 </div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687268/pdf/SYB2-14-307.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38783043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Experimental evidence for constraints in amplitude-timescale co-variation of a biomolecular pulse generating circuit design","authors":"Abhilash Patel, Shaunak Sen","doi":"10.1049/iet-syb.2019.0123","DOIUrl":"10.1049/iet-syb.2019.0123","url":null,"abstract":"<div>\u0000 <p>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 constraints is relatively unclear. Here, the authors address this using experimental measurement of an existing pulse generating incoherent feedforward loop circuit realisation in the context of a standard mathematical model. They characterise the trends of co-variation in the pulse amplitude and rise time computationally by randomly exploring the parameter space. They experimentally measured the co-variation by varying inducers and found that larger amplitude pulses have a slower rise time. They discuss the gap between the experimental measurements and predictions of the standard model, highlighting model additions and other biological factors that might bridge the gap.</p></div>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/79/66/SYB2-14-217.PMC9272780.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38521217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}