Biomedical Data and Applications

  • Amandeep S. Sidhu
  • Tharam S. Dillon

Part of the Studies in Computational Intelligence book series (SCI, volume 224)

Table of contents

  1. Front Matter
  2. Current Trends in Biomedical Data and Applications

    1. Amandeep S. Sidhu, Matthew Bellgard, Tharam S. Dillon
      Pages 1-9
  3. Part I: Biomedical Data

    1. Front Matter
      Pages 11-11
    2. Nicola Cannata, Flavio Corradini, Emanuela Merelli, Francesca Piersigilli, Leonardo Vito
      Pages 13-36
    3. Erika De Francesco, Giuliana Di Santo, Luigi Palopoli, Simona E. Rombo
      Pages 37-54
    4. Amandeep S. Sidhu, Matthew Bellgard
      Pages 55-69
    5. Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan
      Pages 71-141
    6. Arash Shaban-Nejad, Volker Haarslev
      Pages 143-168
    7. Daniele Apiletti, Giulia Bruno, Elisa Ficarra, Elena Baralis
      Pages 169-186
    8. Israel Román Godínez, Itzamá López-Yáñez, Cornelio Yáñez-Márquez
      Pages 187-210
    9. Michele Berlingerio, Francesco Bonchi, Michele Curcio, Fosca Giannotti, Franco Turini
      Pages 211-236
    10. Chang hun You, Lawrence B. Holder, Diane J. Cook
      Pages 237-261
  4. Part II: Biomedical Applications

    1. Front Matter
      Pages 263-263
    2. Jake Y. Chen, Shailaja Taduri, Frank Lloyd
      Pages 265-279
    3. Maja Hadzic, Meifania Chen, Rick Brouwer
      Pages 281-293
    4. Margarita Fernandez, Minaya Villasana, Dan Streja
      Pages 295-315
  5. Back Matter

About this book


Compared with data from general application domains, modern biological data has many unique characteristics. Biological data are often characterized as having large volumes, complex structures, high dimensionality, evolving biological concepts, and insufficient data modelling practices. Over the past several years, bioinformatics has become an all-encompassing term for everything relating to both computer science and biology. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain. The book will become a useful guide learning state-of-the-art development in biomedical data management, data-intensive bioinformatics systems, and other miscellaneous biological database applications. The book addresses various topics in bioinformatics with varying degrees of balance between biomedical data models and their real-world applications.


algorithm bioinformatics biomedical application biomedical applications calculus databases genetic algorithms genome learning linear optimization model modeling multi-agent system multimedia ontology

Editors and affiliations

  • Amandeep S. Sidhu
    • 1
  • Tharam S. Dillon
    • 2
  1. 1.WA Centre for Comparative GenomicsMurdoch UniversityMurdochAustralia
  2. 2.Digital Ecosystems and Business Intelligence InstituteCurtin University of TechnologyPark BentleyAustralia

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-02192-3
  • Online ISBN 978-3-642-02193-0
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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