Query and mining in biological databases

Abstract

In the last decade, biologists experienced a fundamental revolution from traditional researches such as DNA sequence and protein structure research. The biological data is complex, and both the number and the size are growing exponentially. Data evolves more quickly than the technologies developed to interpret the data. This motivated us to conduct researches on the query and mining in biological databases. In this work, we studied the index and similarity search in large DNA sequence databases on desktop PC. We investigated substructure clustering in sequential 3D object datasets, especially protein structures and effectively applied the protein 3D structure patterns as the features in classicifications for remotely homologous proteins.