BlockClust specifications


Unique identifier OMICS_04641
Name BlockClust
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes



Add your version

Publication for BlockClust

BlockClust in publications

PMCID: 5814818
PMID: 29155959
DOI: 10.1093/nar/gkx1115

[…] files to reproduce the analyses described in this manuscript are available at, we assessed the accuracy of serpent by performing a comparison against blockclust (), an unsupervised method that predicts known sncrna families from sncrna-seq data. we evaluated the accuracy to detect known mirnas, trnas and snornas from the gencode annotation () […]

PMCID: 5434267
PMID: 28553651
DOI: 10.1155/2017/9139504

[…] [] is used to scan the long and macro non-protein-coding rnas related to cell-cycle, p53, and stat3 pathways. dge is used for discovering novel polya+noncoding transcripts within human genome []. blockclust [] tries to predict the ncrna modified after its transcription by combining the sequence and secondary structure information with a graph-kernel svm, whose novel thinking lies in a new […]

PMCID: 4437211
PMID: 26042150
DOI: 10.3389/fgene.2015.00188

[…] on wet-lab experiments have confirmed that some trna and snorna can be processed to produce mirna-sized small rna fragments (haussecker et al., ; brameier et al., ). a recently published method, blockclust (videm et al., ), also aims to classify ncrna into mirna, snorna and trna, however unlike alps and deepblockalign, it is based on a graph-kernel method trained on different read profile […]

To access a full list of publications, you will need to upgrade to our premium service.

BlockClust institution(s)
Bioinformatics Group, Department of Computer Science, University of Freiburg, Munich Leukemia Laboratory (MLL), Munich, Centre for Biological Signalling Studies (BIOSS), Centre for Biological Systems Analysis (ZBSA), University of Freiburg, Germany; Centre for Non-coding RNA in Technology and Health, Bagsvaerd, Denmark

BlockClust reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review BlockClust