Google Summer of Code

Overview of the project

In constraint-based metabolic modelling, physical and biochemical constraints define a polyhedral convex set of feasible flux vectors. Uniform sampling of this set provides an unbiased characterization of the metabolic capabilities of a biochemical network. The corresponding polyhedra typically lie in hundreds or thousands of dimensions. Fast convergence to the stationary uniform distribution is crucial from a computational point of view, to enable reliable and tractable sampling of genome-scale biochemical networks.

Tests

The mentors asks for the students to do one or more of the following tests before contacting them.

Here are the aforementioned tests.

Solutions of tests

Click on each task to see the relevant answers.

Easy:

Compile and run VolEsti. Use the R extension to visualize sampling in a polytope.

Medium:

Import the e.coli dataset from bigg and create a matrix in R

Hard:

Support lower dimensional polytopes in volesti and use existing methods to sample from them