89 research outputs found
Soft topographic map for clustering and classification of bacteria
In this work a new method for clustering and building a
topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different
type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria
class by means of the 16S rRNA housekeeping gene. Complete sequences of the gene have been retrieved from the NCBI public database. In the experimental tests the maps show clusters of homologous type strains and present some singular cases potentially due to incorrect classification
or erroneous annotations in the database
Euclidean Distances, soft and spectral Clustering on Weighted Graphs
We define a class of Euclidean distances on weighted graphs, enabling to
perform thermodynamic soft graph clustering. The class can be constructed form
the "raw coordinates" encountered in spectral clustering, and can be extended
by means of higher-dimensional embeddings (Schoenberg transformations).
Geographical flow data, properly conditioned, illustrate the procedure as well
as visualization aspects.Comment: accepted for presentation (and further publication) at the ECML PKDD
2010 conferenc
Hifocon: Object and dimensional coherence and correlation in multidimensional visualization
Abstract. In any multidimensional visualization, some information has to be compromised when projecting multidimensional data to two- or three-dimensional space. We introduce the concepts of dimensional and object coherence and correlation to analyze and classify multidimensional visualization techniques. These concepts are used as principles for our design of Hifocon, a new multidimensional data visualization system.
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