Taxonomic and Phylogenetic Relationships Between Species of the Genus Culex (Diptera: Culicidae) From Brazil Inferred From the Cytochrome c Oxidase I Mitochondrial Gene

Species of the genus Culex Linnaeus have been incriminated as the main vectors of lymphatic filariases and are important vectors of arboviruses, including West Nile virus. Sequences corresponding to a fragment of 478 bp of the cytochrome c oxidase subunit I gene, which includes part of the barcode region, of 37 individuals of 17 species of genus Culex were generated to establish relationships among five subgenera, Culex, Phenacomyia, Melanoconion, Microculex, and Carrollia, and one species of the genus Lutzia that occurs in Brazil. Bayesian methods were employed for the phylogenetic analyses. Results of sequence comparisons showed that individuals identified as Culex dolosus, Culex mollis, and Culex imitator possess high intraspecific divergence (3.1, 2.3, and 3.5%, respectively) when using the Kimura two parameters model. These differences were associated either with distinct morphological characteristics of the male genitalia or larval and pupal stages, suggesting that these may represent species complexes. The Bayesian topology suggested that the genus and subgenus Culex are paraphyletic relative to Lutzia and Phenacomyia, respectively. The cytochrome c oxidase subunit I sequences may be a useful tool to both estimate phylogenetic relationships and identify morphologically similar species of the genus Culex.

HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of Document Collections

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.