Models and algorithms for metabolic networks: elementary modes and precursor sets

Informations générales
Détails de la thèse/HDR
Pierluigi Crescenzi
Khaled Elbassioni
Christian Gautier
Alain Viari
Directeur (pour les thèses)
Marie-France Sagot
Résumé en français
In this PhD, we present some algorithms and complexity results for two general problems that arise in the analysis of a metabolic network: the search for elementary modes of a network and the search for minimal precursors sets.
Elementary modes is a common tool in the study of the cellular characteristic of a metabolic network. An elementary mode can be seen as a minimal set of reactions that can work in steady state independently of the rest of the network. It has therefore served as a mathematical model for the possible metabolic pathways of a cell. Their computation is not trivial and poses computational challenges. We show that some problems, like checking consistency of a network, finding one elementary mode or checking that a set of reactions constitutes a cut are easy problems, giving polynomial algorithms based on LP formulations. We also prove the hardness of central problems like finding a minimum size elementary mode, finding an elementary mode containing two given reactions, counting the number of elementary modes or finding a minimum reaction cut. On the enumeration problem, we show that enumerating all reactions containing one given reaction cannot be done in polynomial total time unless P=NP. This result provides some idea about the complexity of enumerating all the elementary modes.
The search for precursor sets is motivated by discovering which external metabolites are sufficient to allow the production of a given set of target metabolites. In contrast with previous proposals, we present a new approach which is the first to formally consider the use of cycles in the way to produce the target. We present a polynomial algorithm to decide whether a set is a precursor set of a given target. We also show that, given a target set, finding a minimal precursor set is easy but finding a precursor set of minimum size is NP-hard. We further show that finding a solution with minimum size internal supply is NP-hard. We give a simple characterisation of precursors sets by the existence of hyperpaths between the solutions and the target. If we consider the enumeration of all the minimal precursor sets of a given target, we find that this problem cannot be solved in polynomial total time unless P=NP. Despite this result, we present two algorithms that have good performance for medium-size networks.