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MetaMirClust: Discovery and Exploration of Evolutionarily Conserved miRNA Clusters

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Book cover Microarray Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1375))

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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Author information

Authors and Affiliations

  1. Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan, Republic of China

    Wen-Ching Chan

  2. Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, Republic of China

    Wen-Ching Chan & Wen-chang Lin

  3. Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan, Republic of China

    Wen-Ching Chan

Authors
  1. Wen-Ching Chan
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  2. Wen-chang Lin
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Corresponding author

Correspondence to Wen-Ching Chan .

Editor information

Editors and Affiliations

  1. Department of Surgical and Medical Sciences, University “Magna Græcia” of Catanzaro, Catanzaro, Italy

    Pietro Hiram Guzzi

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© 2015 Springer Science+Business Media New York

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Chan, WC., Lin, Wc. (2015). MetaMirClust: Discovery and Exploration of Evolutionarily Conserved miRNA Clusters. In: Guzzi, P. (eds) Microarray Data Analysis. Methods in Molecular Biology, vol 1375. Humana Press, New York, NY. https://doi.org/10.1007/7651_2015_237

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  • DOI: https://doi.org/10.1007/7651_2015_237

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3172-9

  • Online ISBN: 978-1-4939-3173-6

  • eBook Packages: Springer Protocols

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