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Evolutionary computation in bioinformatics /

Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researche...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Fogel, Gary, 1968-, Corne, David
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam ; Boston : Morgan Kaufmann Publishers, �2003.
Colección:Morgan Kaufmann Series in Artificial Intelligence.
Temas:
Acceso en línea:Texto completo
Tabla de Contenidos:
  • An introduction to bioinformatics for computer scientists / David W. Corne and Gary B. Fogel
  • An introduction to evolutionary computation for biologists / Gary B. Fogel and David W. Corne
  • Determining genome sequences from experimental data using evolutionary computation / Jacek Blazewicz and Marta Kasprzak
  • Protein structure alignment using evolutionary computation / Joseph D. Szustakowski and Zhiping Weng
  • Using genetic algorithms for pairwise and multiple sequence alignments / C�edric Notredame
  • On the evolutionary search for solutions to the protein folding problem / Garrison W. Greenwood and Jae-Min Shin
  • Toward effective polypeptide structure prediction with parallel fast messy genetic algorithms / Gary B. Lamont and Laurence D. Merkle
  • Application of evolutionary computation to protein folding with specialized operators / Steffen Schulze-Kremer
  • Identification of coding regions in DNA sequences using evolved neural networks / Gary B. Fogel, Kumar Chellapilla and David B. Fogel
  • Clustering microarray data with evolutionary algorithms / Emanuel Falkenauer and Arnaud Marchand
  • Evolutionary computation and fractal visualization of sequence data / Dan Ashlock and Jim Golden
  • Identifying metabolic pathways and gene regulation networks with evolutionary algorithms / Junji Kitagawa and Hitoshi Iba
  • Evolutionary computational support for the characterization of biological systems / Bogdan Filipi�c and Janez �Strancar
  • Discovery of genetic and environmental interactions in disease data using evolutionary computation / Laetitia Jourdan, Clarisse Dhaenens-Flipo and El-Ghazali Talbi
  • Feature selection methods based on genetic algorithms for in silico drug design / Mark J. Embrechts, Muhsin Ozdemir, Larry Lockwood, Curt Breneman, Kristin Bennett, Dirk Devogelaere and Marcel Rijckaert
  • Interpreting analytical spectra with evolutionary computation / Jem J. Rowland.