A Clustal Alignment Improver using Evolutionary Algorithms

@inproceedings{Thomsen2002ACA,
  title={A Clustal Alignment Improver using Evolutionary Algorithms},
  author={Ren{\'e} Thomsen and Gary B. Fogel and Thiemo Krink},
  year={2002}
}
Multiple sequence alignment (MSA) is a crucial task in bioinformatics. In this study we extended previous work with evolutionary algorithms (EA) by using MSA solutions obtained from the wellknown Clustal V algorithm as a candidate solution seed of the initial EA population. Our results clearly show that EAs can improve the results of Clustal V significantly with marginal computational effort. 
Highly Cited
This paper has 61 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 33 extracted citations

A steady state Genetic Algorithm for Multiple Sequence Alignment

2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI) • 2014

Memetic Algorithms in Bioinformatics

Handbook of Memetic Algorithms • 2012
View 2 Excerpts

62 Citations

051015'03'06'10'14'18
Citations per Year
Semantic Scholar estimates that this publication has 62 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 15 references

A model of evolutionary change in proteins

M. O. Dayhoff, R. M. Schwartz, B. C. Orcutt
Atlas of Protein Sequence and Structure, • 1978
View 6 Excerpts
Highly Influenced

Evolutionary computation techniques for multiple sequence alignment

L. Cai, D. Juedes, E. Liakhovitch
Proceedings of the Second Congress on Evolutionary Computation (CEC- • 2000
View 1 Excerpt

The Protein Data Bank.

Nucleic acids research • 2000
View 2 Excerpts

Similar Papers

Loading similar papers…