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miRNAss
View on CRAN: Click
here
Download and install miRNAss package within the R console
Install from CRAN:
install.packages("miRNAss")
Install from Github:
library("remotes")
install_github("cran/miRNAss")
Install by package version:
library("remotes")
install_version("miRNAss", "1.5")
Attach the package and use:
library("miRNAss")
Maintained by
Cristian Yones
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-06
Latest Update: 2020-10-20
Description:
Machine learning method specifically designed for
pre-miRNA prediction. It takes advantage of unlabeled sequences to improve
the prediction rates even when there are just a few positive examples, when
the negative examples are unreliable or are not good representatives of
its class. Furthermore, the method can automatically search for negative
examples if the user is unable to provide them. MiRNAss can find a good
boundary to divide the pre-miRNAs from other groups of sequences; it
automatically optimizes the threshold that defines the classes boundaries,
and thus, it is robust to high class imbalance. Each step of the method is
scalable and can handle large volumes of data.
How to cite:
Cristian Yones (2017). miRNAss: Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples. R package version 1.5, https://cran.r-project.org/web/packages/miRNAss. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Other R packages that miRNAss depends,
imports, suggests or enhances
Complete documentation for miRNAss
Functions, R codes and Examples using
the miRNAss R package
Some associated functions: adjacencyMatrixKNN . celegans . eigenDecomposition . miRNAss .
Some associated R codes: RcppExports.R . adjacencyMatrixKNN.R . celegans.R . eigenDecomposition.R . miRNAss.R . Full miRNAss package functions and examples
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