Identification of real microRNA precursors with a pseudo structure status composition approach.
Containing about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2015-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4378912?pdf=render |
| _version_ | 1818025592416632832 |
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| author | Bin Liu Longyun Fang Fule Liu Xiaolong Wang Junjie Chen Kuo-Chen Chou |
| author_facet | Bin Liu Longyun Fang Fule Liu Xiaolong Wang Junjie Chen Kuo-Chen Chou |
| author_sort | Bin Liu |
| collection | DOAJ |
| description | Containing about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important regulators of biological processes. Aberrant expression of miRNAs has been observed in many cancers and other disease states, indicating they are deeply implicated with these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Particularly, with the avalanche of RNA sequences generated in the postgenomic age, it is highly desired to develop computational sequence-based methods in this regard. Here two new predictors, called "iMcRNA-PseSSC" and "iMcRNA-ExPseSSC", were proposed for identifying the human pre-microRNAs by incorporating the global or long-range structure-order information using a way quite similar to the pseudo amino acid composition approach. Rigorous cross-validations on a much larger and more stringent newly constructed benchmark dataset showed that the two new predictors (accessible at http://bioinformatics.hitsz.edu.cn/iMcRNA/) outperformed or were highly comparable with the best existing predictors in this area. |
| first_indexed | 2024-12-10T04:18:34Z |
| format | Article |
| id | doaj.art-aab60566f3f04a8882fd09622126c844 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-10T04:18:34Z |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-aab60566f3f04a8882fd09622126c8442022-12-22T02:02:31ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01103e012150110.1371/journal.pone.0121501Identification of real microRNA precursors with a pseudo structure status composition approach.Bin LiuLongyun FangFule LiuXiaolong WangJunjie ChenKuo-Chen ChouContaining about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important regulators of biological processes. Aberrant expression of miRNAs has been observed in many cancers and other disease states, indicating they are deeply implicated with these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Particularly, with the avalanche of RNA sequences generated in the postgenomic age, it is highly desired to develop computational sequence-based methods in this regard. Here two new predictors, called "iMcRNA-PseSSC" and "iMcRNA-ExPseSSC", were proposed for identifying the human pre-microRNAs by incorporating the global or long-range structure-order information using a way quite similar to the pseudo amino acid composition approach. Rigorous cross-validations on a much larger and more stringent newly constructed benchmark dataset showed that the two new predictors (accessible at http://bioinformatics.hitsz.edu.cn/iMcRNA/) outperformed or were highly comparable with the best existing predictors in this area.http://europepmc.org/articles/PMC4378912?pdf=render |
| spellingShingle | Bin Liu Longyun Fang Fule Liu Xiaolong Wang Junjie Chen Kuo-Chen Chou Identification of real microRNA precursors with a pseudo structure status composition approach. PLoS ONE |
| title | Identification of real microRNA precursors with a pseudo structure status composition approach. |
| title_full | Identification of real microRNA precursors with a pseudo structure status composition approach. |
| title_fullStr | Identification of real microRNA precursors with a pseudo structure status composition approach. |
| title_full_unstemmed | Identification of real microRNA precursors with a pseudo structure status composition approach. |
| title_short | Identification of real microRNA precursors with a pseudo structure status composition approach. |
| title_sort | identification of real microrna precursors with a pseudo structure status composition approach |
| url | http://europepmc.org/articles/PMC4378912?pdf=render |
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