An overview of data models for the analysis of biochemical pathways.

TitleAn overview of data models for the analysis of biochemical pathways.
Publication TypeJournal Article
Year of Publication2003
AuthorsDeville, Y., Gilbert D., van Helden J., and Wodak S. J.
JournalBrief Bioinform
Volume4
Issue3
Pagination246-59
Date Published2003 Sep
ISSN1467-5463
KeywordsCell Physiological Phenomena, Computational Biology, Computer Simulation, Models, Biological
Abstract

Biochemical pathways such as metabolic, regulatory or signal transduction pathways can be viewed as interconnected processes forming an intricate network of functional and physical interactions between molecular species in the cell. The amount of information available on such pathways for different organisms is increasing very rapidly. This is offering the possibility of performing various analyses on the structure of the full network of pathways for one organism as well as across different organisms, and has therefore generated interest in developing databases for storing and managing this information. Analysing these networks remains far from straightforward owing to the nature of the databases, which are often heterogeneous, incomplete or inconsistent. Pathway analysis is hence a challenging problem in systems biology and in bioinformatics. Various forms of data models have been devised for the analysis of biochemical pathways. This paper presents an overview of the types of models used for this purpose, concentrating on those concerned with the structural aspects of biochemical networks. In particular, the different types of data models found in the literature are classified using a unified framework. In addition, how these models have been used in the analysis of biochemical networks is described. This enables us to underline the strengths and weaknesses of the different approaches, as well as to highlight relevant future research directions.

Alternate JournalBrief. Bioinformatics
PubMed ID14582519