Skip to main content

A Genetic Algorithm Approach to Solving DNA Fragment Assembly Problem

Buy Article:

$107.14 + tax (Refund Policy)

A genetic algorithm approach for DNA molecule fragment assembly problem is proposed, assuming short, error-less sequences and known total sequence length. This approach maximizes the similarity (overlaps) between given fragments and a candidate sequence. It considers both whole fragments and the single basepair similarities in the sequence. Special genetic operators are designed to speed up the searching process. The efficiency of the proposed approach is demonstrated by numerical experiments for assembled sequence lengths of up to 100 basepairs, with potential for applications for longer sequences or sequences of unknown length as well. Main advantages of the approach are its computational speed and accuracy, which could be helpful when nanotechnology-based high-throughput single-molecule DNA sequencing technologies start to produce large amounts of accurate short sequences.

Keywords: BIOINFORMATICS; DNA SEQUENCING; FRAGMENT ASSEMBLY; GENETIC ALGORITHM

Document Type: Research Article

Publication date: 01 December 2005

More about this publication?
  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
  • Editorial Board
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content