The University of Southampton
Mathematical Sciences

Research project: Molecular and Cellular Biology

Currently Active: 
Yes

We use mathematical models to better understand molecular regulation of cellular dynamics. Our models combine techniques from stochastic analysis, network theory, dynamical systems theory, and reaction-diffusion processes.

Project Overview

Stem cells and tissue engineering

Stem cells and tissue engineering

Stem cell fate decisions are controlled by intrinsically complex molecular regulatory networks, involving a wide variety of protein-protein and protein-DNA interactions. Mathematical models can be used dissect this complexity and elucidate the essential molecular mechanisms that underlie stem cell fate determination and tissue formation. Our work in this area combines mathematical models with experimental data from our collaborators. Since transcription and translation are intrinsically "noisy" processes our models include both deterministic and stochastic mechanisms in order to understand cell-cell variability in stem cell populations.

Biological networks

Biological networks

Cell behaviour is governed by a variety of different complex regulatory networks (for instance, metabolic, transcriptional, signalling, and protein-protein interaction networks). Our work in this area aims to better understand the structural properties of these regulatory networks and the ways in which structural features relate to dynamics and ultimately cell behaviour.

Molecular motors

Molecular motors

Molecular motors are proteins that transform chemical energy into mechanical work on a molecular level, generating forces and leading to motion. We are studying myosin V, a processive molecular motor involved in intracellular transport and found in many animal cell types, particularly neurones. It has two heads that bind to an actin filament and a long neck region that attaches to its cargo, such as vesicles and organelles. The myosin molecule walks hand-over-hand along the actin track via the coordinated binding and release of its heads, fuelled by the hydrolysis of ATP. We use energetics to model the interaction of external load and intramolecular strain with the chemical cycle that governs the stepping action of myosin V, focusing on information transmission between its two heads.   We have compared different myosin V stepping models against available experimental data, and derived analytical results for the expected motor velocity and run length in various classes of discrete stochastic stepping cycle models.  

Related research groups

Applied Mathematics and Theoretical Physics
Mathematics in Biology and Medicine

Staff

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