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A Multi-objective Genetic Algorithm Based Approach to the Optimization of Oligonucleotide Microarray Production Process

  • Filippo Menolascina
  • Vitoantonio Bevilacqua
  • Caterina Ciminelli
  • Mario Nicola Armenise
  • Giuseppe Mastronardi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5227)

Abstract

Microarrays are becoming more and more utilized in the experimental platform in molecular biology. Although rapidly becoming affordable, these micro devices still have quite high production cost which limits their commercial appeal. Here we present a novel multiobjective evolutionary approach to the optimization of the production process of microarray devices mainly aimed at lowering the number of fabrication steps. In order to allow the reader to better understand what we describe we report herein a detailed description of a real-world study case carried out on the most recent microarray platforms of the market leader in this field. A comparative analysis of the most widely used approaches, main potentialities and drawbacks of the proposed approach are presented.

Keywords

Pareto Front Deposition Sequence Microelectrode Array Microarray Production Photolithographic Mask 
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 2008

Authors and Affiliations

  • Filippo Menolascina
    • 1
  • Vitoantonio Bevilacqua
    • 1
  • Caterina Ciminelli
    • 1
  • Mario Nicola Armenise
    • 1
  • Giuseppe Mastronardi
    • 1
  1. 1.Department of Electrotechnics and Electronics Technical University of BariItaly

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