فهرست نشریات علمی دسترسی آزاد ایران

Background: Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoringvarious aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene networkinformation from high-throughput genomic data is an important and difficult task.Objectives: The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlationcoefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is toselect a score threshold and connect all gene pairs whose scores exceed this value.Materials and Methods: In the foundation-application study, we constructed two-way gene networks using nonparametric methods,such as Spearman’s rank correlation coefficient and Blomqvist’s measure, and compared them with Pearson’s correlation coefficient.We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the correspondinggene pair, and obtained two-way interactions using Pearson’s correlation, Spearman’s rank correlation, and Blomqvist’s coefficient.Finally, these methods were compared with Cytoscape, based onBIND, and Gene Ontology, based onmolecular function visual methods;R software version 3.2 and Bioconductor were used to perform these methods.Results: Basedonthe Pearson and Spearman correlations, the results were thesameand wereconfirmedby Cytoscape andGOvisualmethods; however, Blomqvist’s coefficient was not confirmed by visual methods.Conclusions: Some results of the correlation coefficients are not the same with visualization. The reason may be due to the smallnumber of data.