Pregled bibliografske jedinice broj: 415267
Optimization of Parameters in Enzyme Kinetic
Optimization of Parameters in Enzyme Kinetic // HDBMB2008
Osijek, Hrvatska, 2008. str. 37-37 (pozvano predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 415267 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Optimization of Parameters in Enzyme Kinetic
Autori
Jeričević, Željko
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
HDBMB2008
/ - , 2008, 37-37
Skup
Congress of the Croatian Society of Biochemistry and Molecular Biology with International Participation - HDBMB2008
Mjesto i datum
Osijek, Hrvatska, 17.09.2008. - 20.09.2008
Vrsta sudjelovanja
Pozvano predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Optimization; Michaelis-Menten; Hill; PCR; kinetics; computation
Sažetak
Traditionally, biochemists use linearization and straight line fit for determining the parameters in enzyme kinetics. For the Michaelis-Menten kinetics three different linearization methods are commonly used: Lineweaver-Burk, Eadie and Hanes. All of them were developed in pre-computer era and their use today is not justified from the computational point of view. In order to preserve statistical properties of the data, non-linear regression has to be used. This point is illustrated by error propagation and analysis for Michaelis-Menten, Hill and PCR kinetics. The additional requirements imposed on computations by the automatization and processing of the high data volumes will also be presented. The old linearization methodology is still useful, but only for teaching and illustrating purposes. For example, the Lineweaver-Burk plot distinguishes beautifully between competitive and non-competitive inhibition. This opens the question of how much should typical biochemistry student, or more generally bio-sciences student today be familiar with mathematics and computations? The trend in modern biology toward high throughput methods, high interest in system biology, and establishment of new science of Bioinformatics points out that bio-sciences students today have to learn more about mathematics and computations in order be able to follow rapid development of new technologies.
Izvorni jezik
Engleski
Znanstvena područja
Kemija, Biologija, Računarstvo
POVEZANOST RADA
Projekti:
062-0000000-3179 - Klasifikacija proteina metodama eigen-analize
Ustanove:
Medicinski fakultet, Rijeka,
Tehnički fakultet, Rijeka
Profili:
Željko Jeričević
(autor)