Name
Abstract | ||
|---|---|---|
Recently, Almeida and Vinga offered a new approach for the representation of arbitrary discrete sequences, referred to as Universal Sequence Maps (USM), and discussed its applicability to genomic sequence analysis. Their work generalizes and extends Chaos Game Representation (CGR) of DNA for arbitrary discrete sequences.We have considered issues associated with the practical implementation of USMs and offer a variation on the algorithm that: 1) eliminates the overestimation of similar segment lengths, 2) permits the identification of arbitrarily long similar segments in the context of finite word length coordinate representations, 3) uses more computationally efficient operations, and 4) provides a simple conversion for recovering the USM coordinates. Computational performance comparisons and examples are provided.We have shown that the desirable properties of the USM encoding of nucleotide sequences can be retained in a practical implementation of the algorithm. In addition, the proposed implementation enables determination of local sequence identity at increased speed. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1186/1471-2105-3-28 | BMC Bioinformatics |
Keywords | Field | DocType |
algorithms,programming languages,bioinformatics,logic,sequence alignment,nonlinear dynamics,microarrays,computational biology,genome sequence | Sequence alignment,Nonlinear system,Computer science,Theoretical computer science,Chaos game representation,Bioinformatics,Sequence analysis | Journal |
Volume | Issue | ISSN |
3 | 1 | 1471-2105 |
Citations | PageRank | References |
9 | 0.55 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Schwacke | 1 | 17 | 1.05 |
| Jonas S Almeida | 2 | 731 | 42.25 |