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Volume 14 Supplement 1

Computational Intelligence in Bioinformatics and Biostatistics: new trends from the CIBB conference series


Edited by Riccardo Rizzo and Paulo JG Lisboa

Publication of this supplement was funded by the authors.

Seventh International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2010). Go to conference site.

Palermo, Italy16-18 September 2010

  1. Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI) are discovered using either wet lab techniques, such mass spectrom...

    Authors: Giuseppe Agapito, Pietro Hiram Guzzi and Mario Cannataro
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S1
  2. The rationale for gathering information from plants procuring nitrogen through symbiotic interactions controlled by a common genetic program for a sustainable biofuel production is the high energy demanding ap...

    Authors: Luis Carlos Belarmino, Roberta Lane de Oliveira Silva, Nina da Mota Soares Cavalcanti, Nicolas Krezdorn, Ederson Akio Kido, Ralf Horres, Peter Winter, Günter Kahl and Ana Maria Benko-Iseppon
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S2
  3. Supervised machine learning approaches have been recently adopted in the inference of transcriptional targets from high throughput trascriptomic and proteomic data showing major improvements from with respect ...

    Authors: Luigi Cerulo, Vincenzo Paduano, Pietro Zoppoli and Michele Ceccarelli
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S3
  4. The diagnosis of many diseases can be often formulated as a decision problem; uncertainty affects these problems so that many computerized Diagnostic Decision Support Systems (in the following, DDSSs) have bee...

    Authors: Antonio d'Acierno, Massimo Esposito and Giuseppe De Pietro
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S4
  5. We introduce a Knowledge-based Decision Support System (KDSS) in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB) coding the expertise about the proposed scenario, our KDSS is ab...

    Authors: Antonino Fiannaca, Massimo La Rosa, Alfonso Urso, Riccardo Rizzo and Salvatore Gaglio
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S5
  6. Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summa...

    Authors: Raffaele Giancarlo, Giosué Lo Bosco, Luca Pinello and Filippo Utro
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S6
  7. Despite the importance of osmoprotectants, no previous in silico evaluation of high throughput data is available for higher plants. The present approach aimed at the identification and annotation of osmoprotectan...

    Authors: Ederson A Kido, José RC Ferreira Neto, Roberta LO Silva, Luis C Belarmino, João P Bezerra Neto, Nina M Soares-Cavalcanti, Valesca Pandolfi, Manassés D Silva, Alexandre L Nepomuceno and Ana M Benko-Iseppon
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S7
  8. K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total ...

    Authors: Paulo JG Lisboa, Terence A Etchells, Ian H Jarman and Simon J Chambers
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S8
  9. The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New ...

    Authors: Ivan Merelli, Andrea Calabria, Paolo Cozzi, Federica Viti, Ettore Mosca and Luciano Milanesi
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S9
  10. Recently, information derived by correlated mutations in proteins has regained relevance for predicting protein contacts. This is due to new forms of mutual information analysis that have been proven to be mor...

    Authors: Castrense Savojardo, Piero Fariselli, Pier Luigi Martelli and Rita Casadio
    Citation: BMC Bioinformatics 2013 14(Suppl 1):S10

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