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Related Experiment Videos

The mutated subsequence problem and locating conserved genes.

H L Chan1, T W Lam, W K Sung

  • 1Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk

Bioinformatics (Oxford, England)
|March 5, 2005
PubMed
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This study introduces the Mutated Subsequence Problem and a novel algorithm (MSS) for identifying conserved genes across species, even with mutations. MSS effectively finds more conserved genes than existing methods.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Comparative genomics requires methods to identify conserved genes across species.
  • Genome comparisons must account for mutations like reversals and transpositions.

Purpose of the Study:

  • To propose the Mutated Subsequence Problem for whole-genome scale conserved gene identification.
  • To develop an effective algorithm for solving this optimization problem.

Main Methods:

  • Developed the mutated subsequence algorithm (MSS).
  • Evaluated MSS on human/mouse chromosomes and Baculoviridae virus genomes.
  • Compared MSS performance against MUMmer and MaxMinCluster.

Main Results:

Related Experiment Videos

  • MSS effectively identifies conserved genes, revealing >90% of known human/mouse conserved genes.
  • MSS outperforms MUMmer and MaxMinCluster, uncovering 14% and 7% more genes, respectively.
  • A hybrid approach integrating MSS with existing software enhances performance and reliability.

    • Conclusions:

    • The Mutated Subsequence Problem and MSS algorithm offer an effective solution for conserved gene identification.
    • MSS provides a more comprehensive approach to comparative genomics than current tools.
    • Hybrid methods combining MSS with other software show promise for robust genomic analysis.