<tt>miRNAture</tt>—Computational Detection of microRNA Candidates
Homology-based annotation of short RNAs, including microRNAs, is a difficult problem because their inherently small size limits the available information. Highly sensitive methods, including parameter optimized blast, nhmmer, or cmsearch runs designed to increase sensitivity inevitable lead to large...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
|
| Series: | Genes |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4425/12/3/348 |
| _version_ | 1797395048285863936 |
|---|---|
| author | Cristian A. Velandia-Huerto Jörg Fallmann Peter F. Stadler |
| author_facet | Cristian A. Velandia-Huerto Jörg Fallmann Peter F. Stadler |
| author_sort | Cristian A. Velandia-Huerto |
| collection | DOAJ |
| description | Homology-based annotation of short RNAs, including microRNAs, is a difficult problem because their inherently small size limits the available information. Highly sensitive methods, including parameter optimized blast, nhmmer, or cmsearch runs designed to increase sensitivity inevitable lead to large numbers of false positives, which can be detected only by detailed analysis of specific features typical for a RNA family and/or the analysis of conservation patterns in structure-annotated multiple sequence alignments. The miRNAture pipeline implements a workflow specific to animal microRNAs that automatizes homology search and validation steps. The miRNAture pipeline yields very good results for a large number of “typical” miRBase families. However, it also highlights difficulties with atypical cases, in particular microRNAs deriving from repetitive elements and microRNAs with unusual, branched precursor structures and atypical locations of the mature product, which require specific curation by domain experts. |
| first_indexed | 2024-03-09T00:28:44Z |
| format | Article |
| id | doaj.art-bb73d7e28759479e8ceafbd244a58ed5 |
| institution | Directory Open Access Journal |
| issn | 2073-4425 |
| language | English |
| last_indexed | 2024-03-09T00:28:44Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Genes |
| spelling | doaj.art-bb73d7e28759479e8ceafbd244a58ed52023-12-11T18:40:10ZengMDPI AGGenes2073-44252021-02-0112334810.3390/genes12030348<tt>miRNAture</tt>—Computational Detection of microRNA CandidatesCristian A. Velandia-Huerto0Jörg Fallmann1Peter F. Stadler2Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, D-04107 Leipzig, GermanyBioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, D-04107 Leipzig, GermanyBioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, D-04107 Leipzig, GermanyHomology-based annotation of short RNAs, including microRNAs, is a difficult problem because their inherently small size limits the available information. Highly sensitive methods, including parameter optimized blast, nhmmer, or cmsearch runs designed to increase sensitivity inevitable lead to large numbers of false positives, which can be detected only by detailed analysis of specific features typical for a RNA family and/or the analysis of conservation patterns in structure-annotated multiple sequence alignments. The miRNAture pipeline implements a workflow specific to animal microRNAs that automatizes homology search and validation steps. The miRNAture pipeline yields very good results for a large number of “typical” miRBase families. However, it also highlights difficulties with atypical cases, in particular microRNAs deriving from repetitive elements and microRNAs with unusual, branched precursor structures and atypical locations of the mature product, which require specific curation by domain experts.https://www.mdpi.com/2073-4425/12/3/348MicroRNAhomology searchRNA secondary structuremultiple sequence alignmentconsensus structurerepetitive element |
| spellingShingle | Cristian A. Velandia-Huerto Jörg Fallmann Peter F. Stadler <tt>miRNAture</tt>—Computational Detection of microRNA Candidates Genes MicroRNA homology search RNA secondary structure multiple sequence alignment consensus structure repetitive element |
| title | <tt>miRNAture</tt>—Computational Detection of microRNA Candidates |
| title_full | <tt>miRNAture</tt>—Computational Detection of microRNA Candidates |
| title_fullStr | <tt>miRNAture</tt>—Computational Detection of microRNA Candidates |
| title_full_unstemmed | <tt>miRNAture</tt>—Computational Detection of microRNA Candidates |
| title_short | <tt>miRNAture</tt>—Computational Detection of microRNA Candidates |
| title_sort | tt mirnature tt computational detection of microrna candidates |
| topic | MicroRNA homology search RNA secondary structure multiple sequence alignment consensus structure repetitive element |
| url | https://www.mdpi.com/2073-4425/12/3/348 |
| work_keys_str_mv | AT cristianavelandiahuerto ttmirnaturettcomputationaldetectionofmicrornacandidates AT jorgfallmann ttmirnaturettcomputationaldetectionofmicrornacandidates AT peterfstadler ttmirnaturettcomputationaldetectionofmicrornacandidates |