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The expressed MicroRNA-mRNA interactions of Toxoplasma gondii
(Frontiers Media S.A., 2018-01)
MicroRNAs (miRNAs) are involved in post-transcriptional modulation of gene expression and thereby have a large influence on the resulting phenotype. We have previously shown that miRNAs may be involved in the communication ...
Can MiRBase provide positive data for machine learning for the detection of MiRNA hairpins?
(Informationsmanagement in der Biotechnologie e.V., 2013)
Experimental detection and validation of miRNAs is a tedious, time-consuming, and expensive process. Computational methods for miRNA gene detection are being developed so that the number of candidates that need experimental ...
Data mining for microrna gene prediction: On the impact of class imbalance and feature number for microrna gene prediction
(IEEE, 2013)
MicroRNAs (miRNAs) are small, non-coding RNAs which are involved in the posttranscriptional modulation of gene expression. Their short (18-24) single stranded mature sequences are involved in targeting specific genes. It ...
A machine learning approach for microRNA precursor prediction in retro-transcribing virus genomes
(Walter De Gruyter, 2016-12)
Identification of microRNA (miRNA) precursors has seen increased efforts in recent years. The difficulty in experimental detection of pre-miRNAs increased the usage of computational approaches. Most of these approaches ...
On the performance of pre-microRNA detection algorithms
(Nature Publishing Group, 2017-12)
MicroRNAs are crucial for post-transcriptional gene regulation, and their dysregulation has been associated with diseases like cancer and, therefore, their analysis has become popular. The experimental discovery of miRNAs ...
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 ...
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 ...
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 ...
Computational and bioinformatics methods for microRNA gene prediction
(Springer, 2014)
MicroRNAs (miRNAs) have attracted ever-increasing interest in recent years. Since experimental approaches for determining miRNAs are nontrivial in their application, computational methods for the prediction of miRNAs have ...
Machine learning methods for microRNA gene prediction
(Humana Press, 2014)
MicroRNAs (miRNAs) are single-stranded, small, noncoding RNAs of about 22 nucleotides in length, which control gene expression at the posttranscriptional level through translational inhibition, degradation, adenylation, ...
