Application of a simple likelihood ratio approximant to protein sequence classification.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 17090576.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Likelihood ratio approximants (LRA) have been widely used for model comparison in statistics. The present study was undertaken in order to explore their utility as a scoring (ranking) function in the classification of protein sequences. We used a simple LRA-based on the maximal similarity (or minimal distance) scores of the two top ranking sequence classes. The scoring methods (Smith-Waterman, BLAST, local alignment kernel and compression based distances) were compared on datasets designed to test sequence similarities between proteins distantly related in terms of structure or evolution. It was found that LRA-based scoring can significantly outperform simple scoring methods.
Medical subject headings
- Algorithms
- Proteins
- Sequence Alignment
- Sequence Analysis, Protein