Autor(es):
Machado, Daniel 
; Soons, Zita ; Patil, Kiran Raosaheb ; Ferreira, E. C. ; Rocha, I.
Data: 2012
Identificador Persistente: http://hdl.handle.net/1822/21522
Origem: RepositóriUM - Universidade do Minho
Descrição
Motivation: The description of a metabolic network in terms of
elementary (flux) modes (EMs) provides an important framework
for metabolic pathway analysis. However, their application to large
networks has been hampered by the combinatorial explosion in the
number of modes. In this work, we develop a method for generating
random samples of EMs without computing the whole set.
Results: Our algorithm is an adaptation of the canonical basis
approach, where we add an additional filtering step which, at each
iteration, selects a random subset of the new combinations of modes.
In order to obtain an unbiased sample, all candidates are assigned
the same probability of getting selected. This approach avoids the
exponential growth of the number of modes during computation,
thus generating a random sample of the complete set of EMs
within reasonable time. We generated samples of different sizes for
a metabolic network of Escherichia coli, and observed that they
preserve several properties of the full EM set. It is also shown that
EM sampling can be used for rational strain design. A well distributed
sample, that is representative of the complete set of EMs, should be
suitable to most EM-based methods for analysis and optimization of
metabolic networks.
