Metabolic networks and applications to M. tuberculosis

The project involves the modeling of the metabolism of TB. I developed an algorithmic pipeline called MetaMerge, which allowed me to reconcile differences in format, nomenclature, and annotation, between two models of TB metabolism. MONGOOSE, another doctoral project of mine, is a tool for analyzing metabolic network models in exact arithmetic, resulting in consistent, reproducible predictions, something that is currently impossible with any other tools since they rely on floating-point arithmetic.
The student’s role will consist of completing the integration of MetaMerge into the MONGOOSE pipeline, automating the reconciliation of two metabolic network models using machine learning and data mining techniques, and running the algorithm on the metabolic network models of other organisms. This will allow us to create a unified user interface for the two programs, making both programs more user-friendly and accessible, as well as to refine it to work on other organisms. TO BE CONT’D

Faculty Supervisor:

Leonid Chindelevitch

Student:

Partner:

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Biotechnology; Pharmaceuticals

University:

Simon Fraser University

Program:

Globalink Research Award