Applications of Computational Intelligence in Biology

Current Trends and Open Problems

  • Tomasz G. Smolinski
  • Mariofanna G. Milanova
  • Aboul-Ella Hassanien

Part of the Studies in Computational Intelligence book series (SCI, volume 122)

Table of contents

  1. Front Matter
    Pages I-XXVI
  2. Techniques and Methodologies

  3. Current Trends

    1. Dah-Jye Lee, James K. Archibald, Robert B. Schoenberger, Aaron W. Dennis, Dennis K. Shiozawa
      Pages 183-207
    2. John T. Langton, Elizabeth A. Gifford, Timothy J. Hickey
      Pages 231-255
  4. Open Problems

    1. Vladik Kreinovich, Max Shpak
      Pages 281-305
    2. Ying Xie, Jayasimha Katukuri, Vijay V. Raghavan, Tony Presti
      Pages 307-324
    3. Cengiz Günay, Tomasz G. Smolinski, William W. Lytton, Thomas M. Morse, Padraig Gleeson, Sharon Crook et al.
      Pages 325-359
  5. Cognitive Biology

  6. Back Matter
    Pages 423-428

About this book


Computational Intelligence (CI) has been a tremendously active area of - search for the past decade or so. There are many successful applications of CI in many sub elds of biology, including bioinformatics, computational - nomics, protein structure prediction, or neuronal systems modeling and an- ysis. However, there still are many open problems in biology that are in d- perate need of advanced and e cient computational methodologies to deal with tremendous amounts of data that those problems are plagued by. - fortunately, biology researchers are very often unaware of the abundance of computational techniques that they could put to use to help them analyze and understand the data underlying their research inquiries. On the other hand, computational intelligence practitioners are often unfamiliar with the part- ular problems that their new, state-of-the-art algorithms could be successfully applied for. The separation between the two worlds is partially caused by the use of di erent languages in these two spheres of science, but also by the relatively small number of publications devoted solely to the purpose of fac- itating the exchange of new computational algorithms and methodologies on one hand, and the needs of the biology realm on the other. The purpose of this book is to provide a medium for such an exchange of expertise and concerns. In order to achieve the goal, we have solicited cont- butions from both computational intelligence as well as biology researchers.


algorithms behavior biology calculus cognition computational intelligence data analysis evolution evolutionary algorithm genetic algorithms genome intelligence protein protein family visualization

Editors and affiliations

  • Tomasz G. Smolinski
    • 1
  • Mariofanna G. Milanova
    • 2
  • Aboul-Ella Hassanien
    • 3
    • 4
  1. 1.Department of BiologyEmory UniversityAtlantaUSA
  2. 2.Department of Computer ScienceUniversity of Arkansas at Little RockLittle RockUSA
  3. 3.Department of Quantitative Methods and Information Systems College of Business and AdministrationKuwait UniversitySafatKuwait
  4. 4.Department of Information Technology Faculty of Computers and InformationCairo UniversityOrman, GizaEgypt

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-78533-0
  • Online ISBN 978-3-540-78534-7
  • Series Print ISSN 1860-949X
  • Buy this book on publisher's site
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