Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

A mathematical analysis carried out by the Byrne group and colleagues brings new understanding to a recently published kinetic model of ERK phosphorylation.

Extracellular Signal Regulated Kinase (ERK) is an enzyme which plays an important role in multiple cell signalling processes, by catalysing the phosphorylation of a variety of substrates. ERK itself is activated by dual phosphorylation, at two different sites, by a second enzyme called mitogen-activated protein kinase kinase (MEK). The MEK/ERK pathway is involved in processes such as cell division, cell differentiation, and cell death. Mutations in the MEK/ERK pathway are associated with a range of diseases, including cancer; therefore, understanding the mechanisms and kinetics involved in the MEK/ERK pathway is an important step towards its exploitation as a therapeutic target.

Lewis Marsh from the Byrne lab, together with colleagues from the Mathematical Institute and the University of York, have undertaken a mathematical analysis of a recently published systems biology model by Yeung et al. Their previous analysis of the model relied on assumptions that the Byrne lab mathematically interrogated and confirmed using computational algebra and geometry. Marsh and colleagues analysed the kinetics of the ERK dual phosphorylation model with both wild-type and pathologically-relevant MEK mutant datasets with topological data analysis. Building on the work of Yeung et al, this study showcases how algebraic, geometric, and topological analysis methods can not only inform and surpass dynamical and statistical analyses of such models, but also guide future experimental design and research directions.

You can read the full publication in the Bulletin of Mathematical Biology.

Similar stories

Funded DPhil studentships available - apply now for October 2023 entry

Ludwig Oxford research groups are recruiting DPhil candidates for the funded DPhil in Cancer Science, NDM prize studentship and Oxford-MRC Doctoral Training Partnership Industrial Case programmes commencing in October 2023

Mathematical methods for analysing single-cell transcriptomic data

An interdisciplinary collaboration has resulted in the development of three multiscale data methods for the analysis of single-cell transcriptomic data that have advantages over current methods.