Constrained metabolic network analysis: discovering pathways using CP(Graph)
(2005) Workshop on Constraint Based Methods for Bioinformatics, CP2005 — Location: Sitges, Spain (5.October.2005)
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- Abstract
- Biochemical networks { networks composed of the building blocks of the cell and their interactions are qualitative descriptions of the working of the cell. Such networks can be modeled as graphs. Metabolic networks are typical examples of such networks. They are composed of biochemical entities participating to reactions as substrates or products. Such a network can be modeled as a bipartite digraph which nodes are the biochemical entities and reactions and edges are the substrate or product link between an entity and a reaction. Pathways are specic subsets of a metabolic network which were identied as functional processes of cells[1]. As these pathways are known to be working processes of the cell, they can be used to study the metabolic network. One type of metabolic network analysis consists in nding simple paths in the metabolic graph[2{6]. Here we focus on such analysis to discover pathways from a set of their reactions. A potential application is the explanation of DNA chip experiments using a CSP able to solve pathway discovery problems. The study of the metabolic network is constantly evolving and most of the problems are solved with dedicated algorithms. This dedicated approach has the benet of yielding very ecient programs to solve network analysis problems. This approach however has the drawback that it cannot be easily adapted to solve other problems or easily combined to solve combinations of various analyses. In [7, 8], we proposed to use constraint programming to solve constrained path nding problems in metabolic networks. This declarative paradigm allows to easily adapt programs or combine dierent programs. In order to provide a high level modeling language and as the data and results are graphs, we dened a graph computation domain for constraint programming [9]. The two following sections are devoted to a short introduction to CP(Graph) and a description of its application to metabolic network analysis.
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Dooms, G., Deville, Y., & Dupont, P. (2005). Constrained metabolic network analysis: discovering pathways using CP(Graph). Workshop on Constraint Based Methods for Bioinformatics, CP2005, Sitges, Spain. https://hdl.handle.net/2078.5/253965