Package: miRNAss 1.5
Cristian Yones
miRNAss: Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples
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.
Authors:
miRNAss_1.5.tar.gz
miRNAss_1.5.tar.gz(r-4.5-noble)miRNAss_1.5.tar.gz(r-4.4-noble)
miRNAss_1.5.tgz(r-4.4-emscripten)miRNAss_1.5.tgz(r-4.3-emscripten)
miRNAss.pdf |miRNAss.html✨
miRNAss/json (API)
NEWS
# Install 'miRNAss' in R: |
install.packages('miRNAss', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- celegans - Features extracted from hairpins of Caenorhabditis elegans.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:86518bc353. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-linux-x86_64 | OK | Nov 27 2024 |
Exports:adjacencyMatrixKNNeigenDecompositionmiRNAss
Dependencies:clusterCORElearnlatticeMatrixnnetplotrixRcppRcppEigenrpartrpart.plotRSpectra
Readme and manuals
Help Manual
Help page | Topics |
---|---|
MiRNAss: Genome-wide pre-miRNA discovery from few labeled examples | adjacencyMatrixKNN |
Features extracted from hairpins of Caenorhabditis elegans. | celegans |
MiRNAss: Genome-wide pre-miRNA discovery from few labeled examples | eigenDecomposition |
MiRNAss: Genome-wide pre-miRNA discovery from few labeled examples | miRNAss |