{"title":"DerivFit:A Program for Rate Equation Parameter Fitting Using Derivatives","authors":"Rafał Michalski , Wojciech Rode , Andrzej Leś","doi":"10.1006/cbmr.1998.1469","DOIUrl":null,"url":null,"abstract":"<div><p>A C program for fitting parameters in enzymatic rate equations is presented. The<strong>DerivFit</strong>program employs the reaction scheme in the form of ordinary differential equations (ODEs). The kinetic parameters are fitted to the experimental data by minimizing the sum of squared deviations of experimental points from theoretically predicted progress curves. In the minimization process we use the Gradient, Newton, and Marquardt algorithms. The gradients are calculated explicitly by solving a set of additional ODEs that are automatically attached by the program, taking advantage of a general formulation of the basic ODEs that determine the reaction's time course. The program is applied to simple enzymatic systems including slow tight-binding inhibition.</p></div>","PeriodicalId":75733,"journal":{"name":"Computers and biomedical research, an international journal","volume":"31 2","pages":"Pages 71-89"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/cbmr.1998.1469","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and biomedical research, an international journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010480998914690","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A C program for fitting parameters in enzymatic rate equations is presented. TheDerivFitprogram employs the reaction scheme in the form of ordinary differential equations (ODEs). The kinetic parameters are fitted to the experimental data by minimizing the sum of squared deviations of experimental points from theoretically predicted progress curves. In the minimization process we use the Gradient, Newton, and Marquardt algorithms. The gradients are calculated explicitly by solving a set of additional ODEs that are automatically attached by the program, taking advantage of a general formulation of the basic ODEs that determine the reaction's time course. The program is applied to simple enzymatic systems including slow tight-binding inhibition.