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The mutated subsequence problem and locating conserved genes.
1Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk
Bioinformatics (Oxford, England)
|March 5, 2005
Summary
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:
- 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.