Name
Abstract | ||
|---|---|---|
This paper investigates the similarity of two sequences, one of the main issues for fragments clustering and classification when sequencing the genomes of microbial communities directly sampled from natural environment. In this paper, we use the relative entropy as a criterion of similarity of two sequences and discuss its characteristics in DNA sequences. A method for evaluating the relative entropy is presented and applied to the comparison between two sequences. With combination of the relative entropy and the length of variables defined in this paper, the similarity of sequences is easily obtained. The SOM and PCA are applied to cluster subsequences from different genomes. Computer simulations verify that the method works well. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11539087_137 | ICNC (1) |
Keywords | Field | DocType |
similarity analysis,dna sequence,natural environment,microbial community,main issue,cluster subsequence,relative entropy,different genomes,computer simulation | Genome,Computer science,DNA sequencing,Artificial intelligence,Cluster analysis,Similitude,Similarity analysis,Pattern recognition,Bioinformatics,Kullback–Leibler divergence,Machine learning,Principal component analysis,Sequence analysis | Conference |
Volume | ISSN | ISBN |
3610 | 0302-9743 | 3-540-28323-4 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenlu Yang | 1 | 28 | 7.81 |
| Xiongjun Pi | 2 | 1 | 0.76 |
| Liqing Zhang | 3 | 2713 | 181.40 |