The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
miREvo: an integrative microRNA evolutionary analysis platform for next-generation sequencing experiments
Open accessAbstract
Background: MicroRNAs (miRNAs) are small (~19-24nt) non-coding RNAs that play important roles in various biological processes. To date, the next-generation sequencing (NGS) technology has been widely used to discover miRNAs in plants and animals. Although evolutionary analysis is important to reveal the functional dynamics of miRNAs, few computational tools have been developed to analyze the evolution of miRNA sequence and expression across species, especially the newly emerged ones, Results: We developed miREvo, an integrated software platform with a graphical user interface (GUI), to process deep-sequencing data of small RNAs and to analyze miRNA sequence and expression evolution based on the multiple-species whole genome alignments (WGAs). Three major features are provided by miREvo: (i) to identify novel miRNAs in both plants and animals, based on a modified miRDeep algorithm, (ii) to detect miRNA homologs and measure their pairwise evolutionary distances among multiple species based on a WGA, and (iii) to profile miRNA expression abundances and analyze expression divergence across multiple species (small RNA libraries). Moreover, we demonstrated the utility of miREvo with Illumina data sets from Drosophila melanogaster and Arabidopsis, respectively. Conclusion: This work presents an integrated pipline, miREvo, for exploring the expressional and evolutionary dynamics of miRNAs across multiple species. MiREvo is standalone, modular, and freely available at http://evolution.sysu.edu.cn/software/mirevo.htm under the GNU/GPL license.
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Metadata
- Authors
- Wen, M., Shen, Y., Shi, S., & Tang, T.
- Venue
- BMC Bioinformatics
- Published
- 2012-06-21
- Volume
- 13
- Issue
- 1
- Pages
- 140-140
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W2096884048
- Cited by
- 567
- References
- 40
- FWCI
- 6.26
- Type
- journal article
- Language
- en
- Open access
- gold
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