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Topological Metrics in Blast Data Mining: Plasmid and Nitrogen-Fixing Proteins Case Studies

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Bioinformatics Research and Development (BIRD 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 13))

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Abstract

Over the past years, a number of metrics have been introduced to characterize the topology of complex networks. We use these methodologies to analyze networks obtained through Blast data mining. The algorithm we present consists of the following steps: 1- encode results of Blast searches as a distance matrix of e-values; 2- perform entropy-controlled clustering analysis to identify the communities; 3- statistical analysis of the resulting network, 4- gene ontology and data mining in sequence databases to infer the function of the identified clusters. We report on the analysis of two data sets; the first is formed by over 3300 plasmid encoded proteins and the second comprises over 4200 sequences related to nitrogen fixation proteins. In the first case we observed strong selective pressures for horizontal transfer and maintenance of genes encoding proteins for resistance to antibiotics, plasmid stability and conjugal transfer. Nitrogen fixation proteins can be divided on the basis of our results into three different groups: proteins with no paralogs in any of the genomes considered, proteins with paralogs belonging to different metabolic processes (O–paralogs) and proteins with paralogs in other and the same metabolic processes (I/O–paralogs).

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Authors and Affiliations

  1. Computer Laboratory, University of Cambridge, Cambridge, CB3 0FD, United Kingdom

    Pietro Lió

  2. Department of Animal Biology and Genetics, University of Florence, via Romana 17-19, 50125, Firenze, Italy

    Matteo Brilli & Renato Fani

  3. Biometrie et Biologie Evolutive, UMR CNRS 5558, Universite Lyon 1, 43, bvd du 11 novembre, 69622, Villeurbanne Cedex, France

    Matteo Brilli

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  1. Pietro Lió
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Editor information

Mourad Elloumi Josef Küng Michal Linial Robert F. Murphy Kristan Schneider Cristian Toma

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© 2008 Springer-Verlag Berlin Heidelberg

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Lió, P., Brilli, M., Fani, R. (2008). Topological Metrics in Blast Data Mining: Plasmid and Nitrogen-Fixing Proteins Case Studies. In: Elloumi, M., Küng, J., Linial, M., Murphy, R.F., Schneider, K., Toma, C. (eds) Bioinformatics Research and Development. BIRD 2008. Communications in Computer and Information Science, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70600-7_16

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  • DOI: https://doi.org/10.1007/978-3-540-70600-7_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70598-7

  • Online ISBN: 978-3-540-70600-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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