• DocumentCode
    3734143
  • Title

    Microarray data clustering and visualization tool using self-organizing maps

  • Author

    Zach Andrei Marasigan;Abigaile Dionisio;Geoffrey Solano

  • Author_Institution
    Univ. of the Philippines, Manila, Philippines
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Microarray is one of the technologies used in the interdisciplinary science of Biolnformatics. Its primary objective is to discover biological knowledge among genes through their expressions. Gene expressions usually come in large and multidimensional data which makes computational and statistical analyses necessary. Clustering of microarray data is one of these. Grouping similar genes together unfolds relationships of the biological properties of the genes under specific condition and, if supported by visualization, serves as good decision support for researchers. MaSOM is a software that uses Self-Organizing Maps, an Artificial Neural Network suitable both for clustering and for visualization. This tool can be used to analyze large data set by preprocessing, clustering, and visualizing two-color cDNA microarray data. It can therefore aid microarray researchers and practitioners in determining the initial properties of the data they study before proceeding to their actual experimentation onto their data.
  • Keywords
    "Data visualization","Gene expression","Self-organizing feature maps","Cancer","Image color analysis","Clustering algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Information, Intelligence, Systems and Applications (IISA), 2015 6th International Conference on
  • Type

    conf

  • DOI
    10.1109/IISA.2015.7387955
  • Filename
    7387955