MEMOSys: Bioinformatics platform for genome-scale metabolic models

Jens Nielsen,Zlatko Trajanoski,Stephan Pabinger,Rasmus Agren,Robert Rader

doi:10.1186/1752-0509-5-20

Abstract

BackgroundRecent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models.ResultsMEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models.ConclusionsWe have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys.

Highlights

Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects
We have developed a bioinformatics platform for the management, development, and storage of metabolic models
MEMOSys is aimed at the metabolic research community to facilitate the study of existing metabolic models and ease the collaborative development of new ones

Summary

Introduction

Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. One way to leverage sequence data is to use genome-scale metabolic models. Genome-scale metabolic models have already proven to be valuable for strain engineering which aims at improving production yield and stability [10,11]. Their ability to predict the outcome of gene deletions and prognosticate the adaptation of an organism to new nutritional environments makes them a useful instrument to determine the characteristics of alternative flux distributions [12]. Future applications of metabolic models will contribute to the understanding of microbial genomes and may lead to better diagnostic tests and therapies for human diseases [13]

Results

Discussion

Conclusion