A novel meta database for relationships between bioinformatics databases

  • Authors:

  • Emily Richardson;Yingjie Yang;John Hall

  • Affiliations:

  • Institute for Animal Health, Compton, Berkshire, UK;Computational Intelligence, De Montfort University, Leicester, UK;Faculty of Health and Life Sciences, De Montfort University, Leicester, UK

  • Venue:
  • IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
  • Year:
  • 2009

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Abstract

Over the last seven years we have seen an exponential increase in the number of Bioinformatics databases available. These databases are becoming increasingly specialised and are often only known by a small community of users. This paper describes the implementation of a novel meta-database. Rather than simply displaying a list of databases that are available this project has used graphical data in the form of a family tree to show how the databases are related to one another. A general level of relatedness is described using fuzzy sets, this relationship compares every database against all the other databases to see how related they are. It facilitates an automatic construction of the tree when new databases are added.