Koren Murphy
Computing active sets of EFMs for genome scale networks.
Email: [email protected]
Supervisors
Project description
Elementary flux modes (EFMs) are pathways in metabolic networks. This project will compute the active set of EFMs for networks of genome scale size. We will do this through use of experimental metabolic flux data from various experiments.
This approach reduces the dimensionality of the problem. Rather than determining all EFMs, we will determine the active set. This reduces the computational complexity of the problem.
The nature of the problem is very similar to that of the inference of reaction networks from time-series data. Systematic search involves using algorithms such as mixed integer linear programming (MILP). It allows the user to identify the number and nature of chemical reactions occurring. At the same time, it promotes sparse connectivity. It can integrate known structural properties using linear constraints.
Of particular importance is the use of known or identified reaction constraints obtained from process data. This reduces the search space of feasible reactions sets. We are investigating and adapting this approach to the identification of active sets of EFMs. We are using biologically relevant constraints such as those of transcriptional regulation.
We will initially develop the computational approaches using a small network. We will then extend this to genome scale metabolic networks. We will validate the approach by consideration and integration of omics-data (transcriptomic, proteomic data). We will explain variations in experimental flux data using EFMs. We will also consider how to discover pathways that could describe the not yet observed desired behaviour.
Qualifications
MEng Chemical Engineering with Advanced Materials