Database and tools for metabolic network analysis |
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Authors: | Lu Shi Jing Farah Fathiah Muzaffar Shah Mohd Saberi Mohamad Nur Laily Hamran Abdul Hakim Mohamed Salleh Safaai Deris Hany Alashwal |
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Affiliation: | 1. Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia, Skudai, 81310, Malaysia 2. College of Pharmacy, The University of Rhode Island, 7 Greenhouse Rd, South Kingstown, RI, 0288, USA
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Abstract: | Metabolic network analysis has attracted much attention in the area of systems biology. It has a profound role in understanding the key features of organism metabolic networks and has been successfully applied in several fields of systems biology, including in silico gene knockouts, production yield improvement using engineered microbial strains, drug target identification, and phenotype prediction. A variety of metabolic network databases and tools have been developed in order to assist research in these fields. Databases that comprise biochemical data are normally integrated with the use of metabolic network analysis tools in order to give a more comprehensive result. This paper reviews and compares eight databases as well as twenty one recent tools. The aim of this review is to study the different types of tools in terms of the features and usability, as well as the databases in terms of the scope and data provided. These tools can be categorised into three main types: standalone tools; toolbox-based tools; and web-based tools. Furthermore, comparisons of the databases as well as the tools are also provided to help software developers and users gain a clearer insight and a better understanding of metabolic network analysis. Additionally, this review also helps to provide useful information that can be used as guidance in choosing tools and databases for a particular research interest. |
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