Fast and high precision algorithms for optimization in large-scale genomic problems

D. I. Mester, Y. I. Ronin, E. Nevo, A. B. Korol

Research output: Contribution to journalArticlepeer-review


There are several very difficult problems related to genetic or genomic analysis that belong to the field of discrete optimization in a set of all possible orders. With n elements (points, markers, clones, sequences, etc.), the number of all possible orders is n!/2 and only one of these is considered to be the true order. A classical formulation of a similar mathematical problem is the well-known traveling salesperson problem model (TSP). Genetic analogues of this problem include: ordering in multilocus genetic mapping, evolutionary tree reconstruction, building physical maps (contig assembling for overlapping clones and radiation hybrid mapping), and others. A novel, fast and reliable hybrid algorithm based on evolution strategy and guided local search discrete optimization was developed for TSP formulation of the multilocus mapping problems. High performance and high precision of the employed algorithm named guided evolution strategy (GES) allows verification of the obtained multilocus orders based on different computing-intensive approaches (e.g., bootstrap or jackknife) for detection and removing unreliable marker loci, hence, stabilizing the resulting paths. The efficiency of the proposed algorithm is demonstrated on standard TSP problems and on simulated data of multilocus genetic maps up to 1000 points per linkage group.

Original languageEnglish
Pages (from-to)281-290
Number of pages10
JournalComputational Biology and Chemistry
Issue number4
StatePublished - Oct 2004

Bibliographical note

Funding Information:
The author wishes to thank E. Ronin for supplying the simulated data and useful discussions. This research has been partially supported by the Ministry of Absorption, Israel and German-Israeli Cooperation Project (DIP project funded by the BMBF and supported by BMBF's International Bureau at the DLR).


  • Discrete optimization
  • Fast algorithm
  • Multilocus mapping

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Organic Chemistry
  • Computational Mathematics


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