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10.1089/cmb.2014.0073 http://scihub22266oqcxt.onion/10.1089/cmb.2014.0073 C4148055!4148055!25089363     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Comput+Biol 2014 ; 21 (9): 691-8 Nephropedia Template TP {{tp|p=25089363|t=2014. Continuous-Time Markov Chain?Based Flux Analysis in Metabolism |pdf=|usr=}}{{25089363}} gab.com Text Continuous-Time Markov Chain Based Flux Analysis in Metabolism JO: J Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=25089363 #FOAvip Metabolic flux analysis (MFA), a key technology in bioinformatics, is an effective way of analyzing the entire metabolic system by measuring fluxes. Many existing MFA approaches are based on differential equations, which are complicated to be solved mathematically. So MFA requires some simple approaches to investigate metabolism further. In this article, we applied continuous-time Markov chain to MFA, called MMFA approach, and transformed the MFA problem into a set of quadratic equations by analyzing the transition probability of each carbon atom in the entire metabolic system. Unlike the other methods, MMFA analyzes the metabolic model only through the transition probability. This approach is very generic and it could be applied to any metabolic system if all the reaction mechanisms in the system are known. The results of the MMFA approach were compared with several chemical reaction equilibrium constants from early experiments by taking pentose phosphate pathway as an example. Twit Text FOAVip Continuous-Time Markov Chain Based Flux Analysis in Metabolism ????J Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=25089363 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25089363 #FOAvip English Wikipedia <ref>{{Cite pmid|25089363}}</ref> Continuous-Time Markov Chain?Based Flux Analysis in Metabolism #MMPMID25089363 Huo Y; Ji P J Comput Biol 2014[Sep]; 21 (9): 691-8 PMID25089363show ga Metabolic flux analysis (MFA), a key technology in bioinformatics, is an effective way of analyzing the entire metabolic system by measuring fluxes. Many existing MFA approaches are based on differential equations, which are complicated to be solved mathematically. So MFA requires some simple approaches to investigate metabolism further. In this article, we applied continuous-time Markov chain to MFA, called MMFA approach, and transformed the MFA problem into a set of quadratic equations by analyzing the transition probability of each carbon atom in the entire metabolic system. Unlike the other methods, MMFA analyzes the metabolic model only through the transition probability. This approach is very generic and it could be applied to any metabolic system if all the reaction mechanisms in the system are known. The results of the MMFA approach were compared with several chemical reaction equilibrium constants from early experiments by taking pentose phosphate pathway as an example. äContinuous-Time Markov Chain?Based Flux Analysis in Metabolism (epmc).pdf DeepDyve Pubget Overpricing