A comparison of the parameter estimating procedures for the Michaelis-Menten model

✍ Scribed by Shiojenn Tseng; Jyh-Ping Hsu

• Publisher: Elsevier Science
• Year: 1990
• Tongue: English
• Weight: 331 KB
• Volume: 145
• Category: Article
• ISSN: 0022-5193
• DOI: 10.1016/s0022-5193(05)80481-3

✦ Synopsis

The performance of four parameter estimating procedures for the estimation of the adjustable parameters in the Michaelis-Menten model, the maximum initial rate Vmax, and the Michaelis-Menten constant Kin, including Lineweaver & Burk transformation (L-B), Eadie & Hofstee transformation (E-H), Eisenthal & Cornish-Bowden transformation (ECB), and Hsu & Tseng random search (H-T) is compared. The analysis of the simulated data reveals the followings: (i) Vma x can be estimated more precisely than Kin. (ii) The sum of square errors, from the smallest to the largest, follows the sequence H-T, E-H, ECB, L-B. (iii) Considering the sum of square errors, relative error, and computing time, the overall performance follows the sequence H-T, L-B, E-H, ECB, from the best to the worst. (iv) The performance of E-H and ECB are on the same level. (v) L-B and E-H are appropriate for pricesly measured data. H-T should be adopted for data whose error level are high. (vi) Increasing the number of data points has a positive effect on the performance of H-T, and a negative effect on the performance of L-B, E-H, and ECB.