MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs.
MicroRNAs (miRNAs) are a set of short (19∼24 nt) non-coding RNAs that play significant roles as posttranscriptional regulators in animals and plants. The ab initio prediction methods show excellent performance for discovering new pre-miRNAs. While most of these methods can distinguish real pre-miRNA...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2011-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3217989?pdf=render |
| _version_ | 1818197502729388032 |
|---|---|
| author | Ping Xuan Maozu Guo Yangchao Huang Wenbin Li Yufei Huang |
| author_facet | Ping Xuan Maozu Guo Yangchao Huang Wenbin Li Yufei Huang |
| author_sort | Ping Xuan |
| collection | DOAJ |
| description | MicroRNAs (miRNAs) are a set of short (19∼24 nt) non-coding RNAs that play significant roles as posttranscriptional regulators in animals and plants. The ab initio prediction methods show excellent performance for discovering new pre-miRNAs. While most of these methods can distinguish real pre-miRNAs from pseudo pre-miRNAs, few can predict the positions of miRNAs. Among the existing methods that can also predict the miRNA positions, most of them are designed for mammalian miRNAs, including human and mouse. Minority of methods can predict the positions of plant miRNAs. Accurate prediction of the miRNA positions remains a challenge, especially for plant miRNAs. This motivates us to develop MaturePred, a machine learning method based on support vector machine, to predict the positions of plant miRNAs for the new plant pre-miRNA candidates.A miRNA:miRNA* duplex is regarded as a whole to capture the binding characteristics of miRNAs. We extract the position-specific features, the energy related features, the structure related features, and stability related features from real/pseudo miRNA:miRNA* duplexes. A set of informative features are selected to improve the prediction accuracy. Two-stage sample selection algorithm is proposed to combat the serious imbalance problem between real and pseudo miRNA:miRNA* duplexes. The prediction method, MaturePred, can accurately predict plant miRNAs and achieve higher prediction accuracy compared with the existing methods. Further, we trained a prediction model with animal data to predict animal miRNAs. The model also achieves higher prediction performance. It further confirms the efficiency of our miRNA prediction method.The superior performance of the proposed prediction model can be attributed to the extracted features of plant miRNAs and miRNA*s, the selected training dataset, and the carefully selected features. The web service of MaturePred, the training datasets, the testing datasets, and the selected features are freely available at http://nclab.hit.edu.cn/maturepred/. |
| first_indexed | 2024-12-12T01:51:00Z |
| format | Article |
| id | doaj.art-f1a99c41003846f581cbced9c02b4d0c |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-12T01:51:00Z |
| publishDate | 2011-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-f1a99c41003846f581cbced9c02b4d0c2022-12-22T00:42:30ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-01611e2742210.1371/journal.pone.0027422MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs.Ping XuanMaozu GuoYangchao HuangWenbin LiYufei HuangMicroRNAs (miRNAs) are a set of short (19∼24 nt) non-coding RNAs that play significant roles as posttranscriptional regulators in animals and plants. The ab initio prediction methods show excellent performance for discovering new pre-miRNAs. While most of these methods can distinguish real pre-miRNAs from pseudo pre-miRNAs, few can predict the positions of miRNAs. Among the existing methods that can also predict the miRNA positions, most of them are designed for mammalian miRNAs, including human and mouse. Minority of methods can predict the positions of plant miRNAs. Accurate prediction of the miRNA positions remains a challenge, especially for plant miRNAs. This motivates us to develop MaturePred, a machine learning method based on support vector machine, to predict the positions of plant miRNAs for the new plant pre-miRNA candidates.A miRNA:miRNA* duplex is regarded as a whole to capture the binding characteristics of miRNAs. We extract the position-specific features, the energy related features, the structure related features, and stability related features from real/pseudo miRNA:miRNA* duplexes. A set of informative features are selected to improve the prediction accuracy. Two-stage sample selection algorithm is proposed to combat the serious imbalance problem between real and pseudo miRNA:miRNA* duplexes. The prediction method, MaturePred, can accurately predict plant miRNAs and achieve higher prediction accuracy compared with the existing methods. Further, we trained a prediction model with animal data to predict animal miRNAs. The model also achieves higher prediction performance. It further confirms the efficiency of our miRNA prediction method.The superior performance of the proposed prediction model can be attributed to the extracted features of plant miRNAs and miRNA*s, the selected training dataset, and the carefully selected features. The web service of MaturePred, the training datasets, the testing datasets, and the selected features are freely available at http://nclab.hit.edu.cn/maturepred/.http://europepmc.org/articles/PMC3217989?pdf=render |
| spellingShingle | Ping Xuan Maozu Guo Yangchao Huang Wenbin Li Yufei Huang MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. PLoS ONE |
| title | MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. |
| title_full | MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. |
| title_fullStr | MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. |
| title_full_unstemmed | MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. |
| title_short | MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. |
| title_sort | maturepred efficient identification of micrornas within novel plant pre mirnas |
| url | http://europepmc.org/articles/PMC3217989?pdf=render |
| work_keys_str_mv | AT pingxuan maturepredefficientidentificationofmicrornaswithinnovelplantpremirnas AT maozuguo maturepredefficientidentificationofmicrornaswithinnovelplantpremirnas AT yangchaohuang maturepredefficientidentificationofmicrornaswithinnovelplantpremirnas AT wenbinli maturepredefficientidentificationofmicrornaswithinnovelplantpremirnas AT yufeihuang maturepredefficientidentificationofmicrornaswithinnovelplantpremirnas |