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Categorization of species based on their microRNAs employing sequence motifs, information-theoretic sequence feature extraction, and k-mers
(Springer, 2017-12)
Background: Diseases like cancer can manifest themselves through changes in protein abundance, and microRNAs (miRNAs) play a key role in the modulation of protein quantity. MicroRNAs are used throughout all kingdoms and ...
Intersection of MicroRNA and gene regulatory networks and their implication in cancer
(Bentham Science Publishers, 2014-09)
MicroRNAs (miRNAs) have attracted heightened attention for their role as post-transcriptional regulators of gene expression. It has become clear that miRNAs can both up- and downregulate protein expression. According to ...
MicroRNA categorization using sequence motifs and k-mers
(BioMed Central, 2017-03)
Background: Post-transcriptional gene dysregulation can be a hallmark of diseases like cancer and microRNAs (miRNAs) play a key role in the modulation of translation efficiency. Known pre-miRNAs are listed in miRBase, and ...
Computational methods for microRNA target prediction
(Springer, 2014)
MicroRNAs (miRNAs) are important players in gene regulation. The final and maybe the most important step in their regulatory pathway is the targeting. Targeting is the binding of the miRNA to the mature RNA via the RNA-induced ...
Feature selection for microRNA target prediction comparison of one-class feature selection methodologies
(SciTePress, 2016)
Traditionally, machine learning algorithms build classification models from positive and negative examples. Recently, one-class classification (OCC) receives increasing attention in machine learning for problems where the ...
The impact of feature selection on one and two-class classification performance for plant microRNAs
(PeerJ Inc., 2016)
MicroRNAs (miRNAs) are short nucleotide sequences that form a typical hairpin structure which is recognized by a complex enzyme machinery. It ultimately leads to the incorporation of 18-24 nt long mature miRNAs into RISC ...
Feature selection has a large impact on one-class classification accuracy for micrornas in plants
(Hindawi Publishing Corporation, 2016)
MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently ...
Computational methods for ab initio detection of microRNAs
(Frontiers Media, 2012)
MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post-transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by ...
Distinguishing between microRNA targets from diverse species using sequence motifs and K-mers
(SciTePress, 2017-02)
A disease phenotype is often due to dysregulation of gene expression. Post-translational regulation of protein abundance by microRNAs (miRNAs) is, therefore, of high importance in, for example, cancer studies. MicroRNAs ...
