miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants
Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information. We sought to employ the sign...
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| Veröffentlicht in: | Bioinformatics 2011-09, Vol.27 (18), p.2614-2615 |
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| creator | Yang, Xiaozeng Li, Lei |
| description | Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information.
We sought to employ the signature distribution of small RNA reads along the miRNA precursor as a model in plants to profile expression of known miRNA genes and to identify novel ones. A freely available package, miRDeep-P, was developed by modifying miRDeep, which is based on a probabilistic model of miRNA biogenesis in animals, with a plant-specific scoring system and filtering criteria. We have tested miRDeep-P on eight small RNA libraries derived from three plants. Our results demonstrate miRDeep-P as an effective and easy-to-use tool for characterizing the miRNA transcriptome in plants.
http://faculty.virginia.edu/lilab/miRDP/ CONTACT: ll4jn@virginia.edu
Supplementary data are available at Bioinformatics online. |
| doi_str_mv | 10.1093/bioinformatics/btr430 |
| format | Article |
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We sought to employ the signature distribution of small RNA reads along the miRNA precursor as a model in plants to profile expression of known miRNA genes and to identify novel ones. A freely available package, miRDeep-P, was developed by modifying miRDeep, which is based on a probabilistic model of miRNA biogenesis in animals, with a plant-specific scoring system and filtering criteria. We have tested miRDeep-P on eight small RNA libraries derived from three plants. Our results demonstrate miRDeep-P as an effective and easy-to-use tool for characterizing the miRNA transcriptome in plants.
http://faculty.virginia.edu/lilab/miRDP/ CONTACT: ll4jn@virginia.edu
Supplementary data are available at Bioinformatics online.</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1367-4811</identifier><identifier>EISSN: 1460-2059</identifier><identifier>DOI: 10.1093/bioinformatics/btr430</identifier><identifier>PMID: 21775303</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Bioinformatics ; Biological and medical sciences ; Data Mining - methods ; Fundamental and applied biological sciences. Psychology ; Gene Expression ; General aspects ; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) ; MicroRNAs - genetics ; Models, Genetic ; Plants - genetics ; Software ; Transcriptome</subject><ispartof>Bioinformatics, 2011-09, Vol.27 (18), p.2614-2615</ispartof><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c483t-89c4786a562a6b27beafcb7a3ff20cab96558391b3d2df52970d0b93935201d23</citedby><cites>FETCH-LOGICAL-c483t-89c4786a562a6b27beafcb7a3ff20cab96558391b3d2df52970d0b93935201d23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27911,27912</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24488125$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21775303$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Xiaozeng</creatorcontrib><creatorcontrib>Li, Lei</creatorcontrib><title>miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information.
We sought to employ the signature distribution of small RNA reads along the miRNA precursor as a model in plants to profile expression of known miRNA genes and to identify novel ones. A freely available package, miRDeep-P, was developed by modifying miRDeep, which is based on a probabilistic model of miRNA biogenesis in animals, with a plant-specific scoring system and filtering criteria. We have tested miRDeep-P on eight small RNA libraries derived from three plants. Our results demonstrate miRDeep-P as an effective and easy-to-use tool for characterizing the miRNA transcriptome in plants.
http://faculty.virginia.edu/lilab/miRDP/ CONTACT: ll4jn@virginia.edu
Supplementary data are available at Bioinformatics online.</description><subject>Bioinformatics</subject><subject>Biological and medical sciences</subject><subject>Data Mining - methods</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gene Expression</subject><subject>General aspects</subject><subject>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</subject><subject>MicroRNAs - genetics</subject><subject>Models, Genetic</subject><subject>Plants - genetics</subject><subject>Software</subject><subject>Transcriptome</subject><issn>1367-4803</issn><issn>1367-4811</issn><issn>1460-2059</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkMtKxDAUQIMojq9PULIRV9U828TdMD5BVAZdlyRNNdI2Ncksxq83MqPiytW9F859HQAOMTrFSNIz7bwbWh96lZyJZzoFRtEG2MG0rAomMN78yRGdgN0Y3xBCHPFyG0wIripOEd0B897NL6wdi8dzqKDx_bhIeaIfVAeT9x3MK6DK1fLDDS8wvVrYOxP8_H4KU1BDNMGNyfcWugGOnRpS3AdbreqiPVjHPfB8dfk0uynuHq5vZ9O7wjBBUyGkYZUoFS-JKjWptFWt0ZWibUuQUVqWnAsqsaYNaVpOZIUapCWVlBOEG0L3wMlq7hj8-8LGVPcuGtvlI6xfxFpizgSXHP1LCiGQJIyxTPIVmV-MMdi2HoPrVVjWGNVf3uu_3uuV99x3tN6w0L1tfrq-RWfgeA2oaFTXZnXGxV-OMSEw4fQTa-yQ5w</recordid><startdate>20110915</startdate><enddate>20110915</enddate><creator>Yang, Xiaozeng</creator><creator>Li, Lei</creator><general>Oxford University Press</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>20110915</creationdate><title>miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants</title><author>Yang, Xiaozeng ; Li, Lei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c483t-89c4786a562a6b27beafcb7a3ff20cab96558391b3d2df52970d0b93935201d23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Bioinformatics</topic><topic>Biological and medical sciences</topic><topic>Data Mining - methods</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gene Expression</topic><topic>General aspects</topic><topic>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</topic><topic>MicroRNAs - genetics</topic><topic>Models, Genetic</topic><topic>Plants - genetics</topic><topic>Software</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Xiaozeng</creatorcontrib><creatorcontrib>Li, Lei</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Xiaozeng</au><au>Li, Lei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2011-09-15</date><risdate>2011</risdate><volume>27</volume><issue>18</issue><spage>2614</spage><epage>2615</epage><pages>2614-2615</pages><issn>1367-4803</issn><eissn>1367-4811</eissn><eissn>1460-2059</eissn><abstract>Ultra-deep sampling of small RNA libraries by next-generation sequencing has provided rich information on the microRNA (miRNA) transcriptome of various plant species. However, few computational tools have been developed to effectively deconvolute the complex information.
We sought to employ the signature distribution of small RNA reads along the miRNA precursor as a model in plants to profile expression of known miRNA genes and to identify novel ones. A freely available package, miRDeep-P, was developed by modifying miRDeep, which is based on a probabilistic model of miRNA biogenesis in animals, with a plant-specific scoring system and filtering criteria. We have tested miRDeep-P on eight small RNA libraries derived from three plants. Our results demonstrate miRDeep-P as an effective and easy-to-use tool for characterizing the miRNA transcriptome in plants.
http://faculty.virginia.edu/lilab/miRDP/ CONTACT: ll4jn@virginia.edu
Supplementary data are available at Bioinformatics online.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><pmid>21775303</pmid><doi>10.1093/bioinformatics/btr430</doi><tpages>2</tpages><oa>free_for_read</oa></addata></record> |
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| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Oxford Journals Open Access Collection; PubMed Central; Alma/SFX Local Collection |
| subjects | Bioinformatics Biological and medical sciences Data Mining - methods Fundamental and applied biological sciences. Psychology Gene Expression General aspects Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) MicroRNAs - genetics Models, Genetic Plants - genetics Software Transcriptome |
| title | miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants |
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