Karen T. Fields, Noel T. Fortun, Geoffrey A. Solano, Angelyn R. Lao
{"title":"CRNet Translator: Building GMA, S-System Models and Chemical Reaction Networks of Disease and Metabolic Pathways","authors":"Karen T. Fields, Noel T. Fortun, Geoffrey A. Solano, Angelyn R. Lao","doi":"10.1109/IISA50023.2020.9284412","DOIUrl":null,"url":null,"abstract":"Ordinary Differential Equation (ODE) requires the use of differential equations to describe the dynamically changing phenomena, evolution, and variation and Chemical Reaction Network (CRN) is a model that gives a more general interpretation of biochemical networks as it ties aspects of reaction network structure in a precise way. In this study, these computational approaches can be used to model biological networks in the form of disease or metabolic pathways. Given the availability of data from Kyoto Encyclopedia of Genes and Genomes (KEGG), the application can convert the selected pathways to S-system or Generalized Mass-Action (GMA) ODE, and this ODE can be extended to its corresponding CRN to show more intimate relationships between network structure and basic phenomena of biological functions.","PeriodicalId":109238,"journal":{"name":"2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISA50023.2020.9284412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ordinary Differential Equation (ODE) requires the use of differential equations to describe the dynamically changing phenomena, evolution, and variation and Chemical Reaction Network (CRN) is a model that gives a more general interpretation of biochemical networks as it ties aspects of reaction network structure in a precise way. In this study, these computational approaches can be used to model biological networks in the form of disease or metabolic pathways. Given the availability of data from Kyoto Encyclopedia of Genes and Genomes (KEGG), the application can convert the selected pathways to S-system or Generalized Mass-Action (GMA) ODE, and this ODE can be extended to its corresponding CRN to show more intimate relationships between network structure and basic phenomena of biological functions.