Name
Abstract | ||
|---|---|---|
The phylogenetic classification of DNA fragments from a variety of microorganisms is often performed in metagenomic analysis to understand the taxonomic composition of microbial communities. A faster method for taxonomic classification based on metagenomic reads is required with the improvement of DNA sequencer's throughput in recent years. In this research we focus on naive Bayes, which can quickly classify organisms with sufficient accuracy, and we have developed an acceptably fast, yet more accurate classification method using improved naive Bayes, Weightily Averaged One-Dependence Estimators (WAODE). Additionally, we accelerated WAODE classification by introducing a cutoff for the mutual information content, and achieved a 20 times faster classification speed while keeping comparable prediction accuracy. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-09330-7_32 | INTELLIGENT COMPUTING IN BIOINFORMATICS |
Keywords | Field | DocType |
Metagenomic analysis, phylogenetic classification, naive Bayes | Phylogenetic nomenclature,Biological classification,Pattern recognition,Naive Bayes classifier,Computer science,Metagenomics,Mutual information,Artificial intelligence,DNA sequencer,Machine learning,Estimator | Conference |
Volume | ISSN | Citations |
8590 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuki Komatsu | 1 | 0 | 0.34 |
| Takashi Ishida | 2 | 41 | 6.58 |
| Yutaka Akiyama | 3 | 172 | 37.62 |