Mirsynergy statistics

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Mirsynergy specifications


Unique identifier OMICS_12516
Name Mirsynergy
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.16.0
Stability Stable
RColorBrewer, parallel, graphics, BiocGenerics, Matrix, utils, grDevices, ggplot2, RUnit, scales, knitr, reshape, igraph, gridExtra, R(>=3.0.2), glmnet
Maintained Yes



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  • person_outline Yue Li <>

Publication for Mirsynergy

Mirsynergy in publications

PMCID: 5259869
PMID: 28155675
DOI: 10.1186/s12918-016-0357-1

[…] modules) [], but using a non-convex algorithm. this method may result in unstable outcomes because of its random initialization. then, li et al. developed a two-stage overlap clustering method, mirsynergy []. this method improves the efficiency substantially, and importantly, facilitates the setting of predefined parameters. however, this method does not consider the relations […]

PMCID: 4331711
PMID: 25707620
DOI: 10.1186/1471-2164-16-S2-S11

[…] the time complexity of these algorithms is quadratic to both the number of mirna and mrna multiplied by the total number of modules per iteration. li et al. (2014) proposed a novel method called mirsynergy to detect mirna regulatory modules (mirms) by integrating mrna/mirna expression profiles, target site information and gene-gene interaction to form mirms, which can automatically determine […]

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Mirsynergy institution(s)
Department of Computer Science, University of Toronto, Toronto, ON, Canada; The Donnelly Centre, University of Toronto, Toronto, ON, Canada; College of Information Science and Engineering, Hunan University, Changsha, Hunan, China; Banting and Best Department of Medical Research and Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
Mirsynergy funding source(s)
This work is funded by Natural Sciences and Engineering Research Council (NSERC) Canada Graduate Scholarship, supported by Ontario Research Fund - Global Leader (Round 2), an NSERC grant, and by the National Natural Science Foundation of China (Grant NO. 61240046) and Hunan Provincial Natural Science Foundation of China (Grant NO.13JJ2017).

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