Veracity of the archive : a research approach to the collection and verification of urban morphological records using qualitative data analysis software

Critical to the research of urban morphologists is the availability of historical records that document the urban transformation of the study area. However, thus far little work has been done towards an empirical approach to the validation of archival data in this field. Outlined in this paper, therefore, is a new methodology for validating the accuracy of archival records and mapping data, accrued through the process of urban morphological research, so as to establish a reliable platform from which analysis can proceed. The paper particularly addresses the problems of inaccuracies in existing curated historical information, as well as errors in archival research by student assistants, which together give rise to unacceptable levels of uncertainty in the documentation. The paper discusses the problems relating to the reliability of historical information, demonstrates the importance of data verification in urban morphological research, and proposes a rigorous method for objective testing of collected archival data through the use of qualitative data analysis software.

Some comparison on whole-proteome phylogeny of large dsDNA viruses based on dynamical language approach and feature frequency profiles method

There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among them, CVTree method, feature frequency profiles method and dynamical language approach were used to investigate the whole-proteome phylogeny of large dsDNA viruses. Using the data set of large dsDNA viruses from Gao and Qi (BMC Evol. Biol. 2007), the phylogenetic results based on the CVTree method and the dynamical language approach were compared in Yu et al. (BMC Evol. Biol. 2010). In this paper, we first apply dynamical language approach to the data set of large dsDNA viruses from Wu et al. (Proc. Natl. Acad. Sci. USA 2009) and compare our phylogenetic results with those based on the feature frequency profiles method. Then we construct the whole-proteome phylogeny of the larger dataset combining the above two data sets. According to the report of The International Committee on the Taxonomy of Viruses (ICTV), the trees from our analyses are in good agreement to the latest classification of large dsDNA viruses.