Unknown

Dataset Information

0

Analysis of algebraic weighted least-squares estimators for enzyme parameters.


ABSTRACT: An algorithm for the least-squares estimation of enzyme parameters Km and Vmax. is proposed and its performance analysed. The problem is non-linear, but the algorithm is algebraic and does not require initial parameter estimates. On a spreadsheet program such as MINITAB, it may be coded in as few as ten instructions. The algorithm derives an intermediate estimate of Km and Vmax. appropriate to data with a constant coefficient of variation and then applies a single reweighting. Its performance using simulated data with a variety of error structures is compared with that of the classical reciprocal transforms and to both appropriately and inappropriately weighted direct least-squares estimators. Three approaches to estimating the standard errors of the parameter estimates are discussed, and one suitable for spreadsheet implementation is illustrated.

SUBMITTER: Jones ME 

PROVIDER: S-EPMC1132043 | biostudies-other | 1992 Dec

REPOSITORIES: biostudies-other

Similar Datasets

| S-EPMC9253927 | biostudies-literature
| S-EPMC5372833 | biostudies-literature
| S-EPMC5701264 | biostudies-literature
| S-EPMC6545287 | biostudies-literature
| S-EPMC2988831 | biostudies-other
| S-EPMC5483398 | biostudies-literature
| S-EPMC8463630 | biostudies-literature
| S-EPMC7070265 | biostudies-literature
| S-EPMC8165794 | biostudies-literature
| S-EPMC4912936 | biostudies-literature