Name
Title | ||
|---|---|---|
Prediction of small non-coding RNA in bacterial genomes using support vector machines |
Abstract | ||
|---|---|---|
Small non-coding RNA genes have been shown to play important regulatory roles in a variety of cellular processes, but prediction of non-coding RNA genes is a great challenge, using either an experimental or a computational approach, due to the characteristics of sRNAs, which are that sRNAs are small in size, are not translated into proteins and show variable stability. Most known sRNAs have been identified in Escherichia coli and have been shown to be conserved in closely related organisms. We have developed an integrative approach that searches highly conserved intergenic regions among related bacterial genomes for combinations of characteristics that have been extracted from known E. coli sRNA genes. Support vector machines (SVM) were then used with these characteristics to predict novel sRNA genes. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.eswa.2010.02.058 | Expert Syst. Appl. |
Keywords | Field | DocType |
srna gene,novel srna gene,support vector machine,related bacterial genomes,conserved intergenic region,support vector machines,integrative approach,computational approach,e. coli,known srnas,escherichia coli,expert systems,bioinformatics,machine learning,small non-coding rna,non-coding rna,non-coding rna gene,expert system,non coding rna,bacterial genome | RNA,Gene,Computer science,Artificial intelligence,Intergenic region,Computational biology,Escherichia coli,Bacterial genome size,Support vector machine,Transfer RNA,Bioinformatics,Non-coding RNA,Machine learning | Journal |
Volume | Issue | ISSN |
37 | 8 | Expert Systems With Applications |
Citations | PageRank | References |
2 | 0.38 | 6 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tzu-Hao Chang | 1 | 145 | 11.92 |
| Li-Ching Wu | 2 | 15 | 5.03 |
| Jun-Hong Lin | 3 | 24 | 3.79 |
| Hsien-Da Huang | 4 | 835 | 63.83 |
| Baw-Jhiune Liu | 5 | 193 | 38.12 |
| Kuang-Fu Cheng | 6 | 20 | 3.85 |
| Jorng-Tzong Horng | 7 | 541 | 67.78 |