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Adenine: A HPC-Oriented Tool for Biological Data Exploration

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Book cover Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2017)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10834))

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Abstract

adenine is a machine learning framework designed for biological data exploration and visualization. Its goal is to help bioinformaticians achieving a first and quick overview of the main structures underlying their data. This software tool encompasses state-of-the-art techniques for missing values imputing, data preprocessing, dimensionality reduction and clustering. adenine has a scalable architecture which seamlessly work on single workstations as well as on high-performance computing facilities. adenine is capable of generating publication-ready plots along with quantitative descriptions of the results. In this paper we provide an example of exploratory analysis on a publicly available gene expression data set of colorectal cancer samples. The software and its documentation are available at https://github.com/slipguru/adenine under FreeBSD license.

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Notes

  1. 1.

    http://mpi-forum.org/.

  2. 2.

    http://slipguru.github.io/adenine.

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Acknowledgments

We would like to acknowledge Dr. Davide Marini for his help, assistance and support in using the high-performance computing (HPC) systems operated by the Ligurian Cluster for Marine Technologies (DLTM - http://www.dltm.it).

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Authors and Affiliations

  1. Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, 16146, Genoa, Italy

    Samuele Fiorini, Federico Tomasi, Margherita Squillario & Annalisa Barla

Authors
  1. Samuele Fiorini
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  2. Federico Tomasi
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  3. Margherita Squillario
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  4. Annalisa Barla
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Corresponding author

Correspondence to Samuele Fiorini .

Editor information

Editors and Affiliations

  1. University of Cagliari, Cagliari, Italy

    Massimo Bartoletti

  2. University of Genova, Genoa, Italy

    Annalisa Barla

  3. University of Stirling, Stirling, UK

    Andrea Bracciali

  4. Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany

    Gunnar W. Klau

  5. Houston Methodist Research Institute, Houston, TX, USA

    Leif Peterson

  6. University of Udine, Udine, Italy

    Alberto Policriti

  7. University of Salerno, Fisciano, Italy

    Roberto Tagliaferri

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Fiorini, S., Tomasi, F., Squillario, M., Barla, A. (2019). Adenine: A HPC-Oriented Tool for Biological Data Exploration. In: Bartoletti, M., et al. Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2017. Lecture Notes in Computer Science(), vol 10834. Springer, Cham. https://doi.org/10.1007/978-3-030-14160-8_6

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  • DOI: https://doi.org/10.1007/978-3-030-14160-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14159-2

  • Online ISBN: 978-3-030-14160-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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