Scientific and Statistical Database Management, International Conference on (2003)
Cambridge, Massachusetts, USA
July 9, 2003 to July 11, 2003
Wolfgang Lehner , Dresden University of Technology, Germany
Alexander Hinneburg , University of Halle, Germany
The progress in genome research demands for an adequate infrastructure to analyse the data sets. Database systems reflect a key technology to organize data and speed up the analysis process.<div></div> This paper discusses the role of a relational database system based on the problem of finding frequent substructures in multi-dimensional protein databases. The specific problem consists of producing a set of association rules regarding frequent substructures with different lengths and gaps between the amino acid residues of a protein. From a database point of view, the process of finding association rules building the base for a more in-depth analysis of the data material is split into two parts. The first part performs a discretization of the conformational angle space of a single amino acid residue by computing the nearest neighbour of a given set of representatives. The second part consists in adapting a well-known association rule algorithm to determine the frequent substructures. Both steps within this comprehensive analysis task requires substantial support of the underlying database in order to reduce the programming overhead at the application level.
Wolfgang Lehner, Alexander Hinneburg, "Database Support for 3D-Protein Data Set Analysis", Scientific and Statistical Database Management, International Conference on, vol. 00, no. , pp. 161, 2003, doi:10.1109/SSDM.2003.1214977