| Chapter title |
MetaMirClust: Discovery and Exploration of Evolutionarily Conserved miRNA Clusters.
|
|---|---|
| Chapter number | 237 |
| Book title |
Microarray Data Analysis
|
| Published in |
Methods in molecular biology, April 2015
|
| DOI | 10.1007/7651_2015_237 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3172-9, 978-1-4939-3173-6
|
| Authors |
Chan, Wen-Ching, Lin, Wen-Chang, Wen-Ching Chan, Wen-chang Lin, Lin, Wen-chang |
| Abstract |
Recent emerging studies suggest that a substantial fraction of microRNA (miRNA) genes is likely to form clusters in terms of evolutionary conservation and biological implications, posing a significant challenge for the research community and shifting the bottleneck of scientific discovery from miRNA singletons to miRNA clusters. In addition, the advance in molecular sequencing technique such as next-generation sequencing (NGS) has facilitated researchers to comprehensively characterize miRNAs with low abundance on genome-wide scale in multiple species. Taken together, a large scale, cross-species survey of grouped miRNAs based on genomic location would be valuable for investigating their biological functions and regulations in an evolutionary perspective. In the present chapter, we describe the application of effective and efficient bioinformatics tools on the identification of clustered miRNAs and illustrate how to use the recently developed Web-based database, MetaMirClust ( http://fgfr.ibms.sinic.aedu.tw/MetaMirClust ) to discover evolutionarily conserved pattern of miRNA clusters across metazoans. |
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Mendeley readers
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| Other | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Lecturer | 1 | 5% |
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| Other | 3 | 15% |
| Unknown | 4 | 20% |
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| Neuroscience | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 5 | 25% |