Now showing items 1-4 of 4
Categorization of species based on their microRNAs employing sequence motifs, information-theoretic sequence feature extraction, and k-mers
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 ...
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 ...
Delineating the impact of machine learning elements in pre-microRNA detection
(PeerJ Inc., 2017)
Gene regulation modulates RNA expression via transcription factors. Posttranscriptional gene regulation in turn influences the amount of protein product through, for example, microRNAs (miRNAs). Experimental establishment ...
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 ...