A simple feature representation vector for phylogenetic analysis of DNA sequences
Abstract In this study, a simple 4 k -dimension feature representation vector is proposed to reconstruct phylogenetic trees, where k is the length of a word. The vector is composed of elements which characterize the relative difference of biological sequence from sequence generated by an independent random process. In addition, the variance of a vector which is obtained by averaging every column of feature representation matrix is employed to determine appropriate word length. In our experiments, reliable results can always be generated when word length is 7 which appears to be of lower computational complexity. Phylogenetic trees of 24 transferrins and 48 Hepatitis E viruses reconstructed at word length 6 are in good agreements with previous study, it shows that our method is efficient and powerful.
Today most of the data exchanged between information systems is done with the help of the XML syntax. Unfortunately when these data have to be integrated, the integration becomes difficult because of the semantics' heterogeneity. Consequently, leading researches in the domain of database systems are moving to semantic model in order to store data and its semantics definition. To benefit from these new systems and technologies, and to integrate different data sources, a flexible method consists in populating an existing OWL ontology from XML data. In paper we present such a method based on the definition of a graph which represents rules that drive the populating process. The graph of rules facilitates the mapping definition that consists in mapping elements from an XSD schema to the elements of the OWL schema.