Toward a Semantic Framework for the Querying, Mining and Visualization of Cancer Microenvironment Data

  • Michelangelo Ceci
  • Fabio Fumarola
  • Pietro Hiram Guzzi
  • Federica Mandreoli
  • Riccardo Martoglia
  • Elio Masciari
  • Massimo Mecella
  • Wilma Penzo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7451)


Over the last decade, the advances in the high-throughput omic technologies have given the possibility to profile tumor cells at different levels, fostering the discovery of new biological data and the proliferation of a large number of bio-technological databases. In this paper we describe a framework for enabling the interoperability among different biological data sources and for ultimately supporting expert users in the complex process of extraction, navigation and visualization of the precious knowledge hidden in such a huge quantity of data. The system will be used in a pilot study on the Multiple Myeloma (MM).


Multiple Myeloma Short Time Series Graph Query Semantic Framework Network Alignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Michelangelo Ceci
    • 4
  • Fabio Fumarola
    • 4
  • Pietro Hiram Guzzi
    • 3
  • Federica Mandreoli
    • 6
  • Riccardo Martoglia
    • 6
  • Elio Masciari
    • 1
  • Massimo Mecella
    • 2
  • Wilma Penzo
    • 5
  1. 1.ICAR-CNRItaly
  2. 2.La Sapienza UniversityItaly
  3. 3.Magna Graecia UniversityItaly
  4. 4.University of BariItaly
  5. 5.DEISUniversity of BolognaItaly
  6. 6.DIIUniversity of Modena and Reggio EmiliaItaly

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