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Swarming along the evolutionary branches sheds light on genome rearrangement scenarios
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 11th Annual conference on Genetic and evolutionary computation table of contents
Montreal, Québec, Canada
SESSION: Track 3: bioinformatics and computational biology table of contents
Pages 241-246  
Year of Publication: 2009
ISBN:978-1-60558-325-9
Authors
Nikolay Vyahhi  St. Petersburg State University, St. Petersburg, Russian Fed.
Adrien Goëffon  INRIA, Bordeaux, France
Macha Nikolski  CNRS / LaBRI, Bordeaux, France
David James Sherman  INRIA, Bordeaux, France
Sponsors
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

A genome rearrangement scenario describes a series of chromosome fusion, fission, and translocation operations that suffice to rewrite one genome into another. Exact algorithmic methods for this important problem focus on providing one solution, while the set of distance-wise equivalent scenarios is very large. Moreover, no criteria for filtering for biologically plausible scenarios is currently proposed. We present an original metaheuristic method that uses Ant Colony Optimization to randomly explore the space of optimal and suboptimal rearrangement scenarios. It improves on the state of the art both by permitting large-scale enumeration of optimal scenarios, and by labeling each with metrics that can be used for post-processing filtering based on biological constraints.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Nikolay Vyahhi: colleagues
Adrien Goëffon: colleagues
Macha Nikolski: colleagues
David James Sherman: colleagues