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Volume 17 Supplement 11

Selected articles from the 11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2014)

Research

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they were not involved in the peer review process for any articles that they are an author of and that they have no other competing interests.

Cambridge, UK26-28 June 2014

Conference website

Edited by Alessandro Nonis, Clelia Di Serio, Pietro Lio', Roberto Tagliaferri and Riccardo Rizzo.

  1. Pose generation error is usually quantified as the difference between the geometry of the pose generated by the docking software and that of the same molecule co-crystallised with the considered protein. Surpr...

    Authors: Hongjian Li, Kwong-Sak Leung, Man-Hon Wong and Pedro J. Ballester
    Citation: BMC Bioinformatics 2016 17(Suppl 11):308
    Content type: Research Published on:

  2. Haplotype phasing is an important problem in the analysis of genomics information. Given a set of DNA fragments of an individual, it consists of determining which one of the possible alleles (alternative forms...

    Authors: Andrea Bracciali, Marco Aldinucci, Murray Patterson, Tobias Marschall, Nadia Pisanti, Ivan Merelli and Massimo Torquati
    Citation: BMC Bioinformatics 2016 17(Suppl 11):342
    Content type: Research Published on:

  3. MicroRNAs (miRNAs) are small non-coding RNA sequences with regulatory functions to post-transcriptional level for several biological processes, such as cell disease progression and metastasis. MiRNAs interact ...

    Authors: Antonino Fiannaca, Massimo La Rosa, Laura La Paglia, Riccardo Rizzo and Alfonso Urso
    Citation: BMC Bioinformatics 2016 17(Suppl 11):321
    Content type: Research Published on:

  4. RNA sequencing takes advantage of the Next Generation Sequencing (NGS) technologies for analyzing RNA transcript counts with an excellent accuracy. Trying to interpret this huge amount of data in biological in...

    Authors: Daniela Evangelista, Kumar Parijat Tripathi and Mario Rosario Guarracino
    Citation: BMC Bioinformatics 2016 17(Suppl 11):360
    Content type: Research Published on:
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BMC Bioinformatics

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