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Improving the quality of positive datasets for the establishment of machine learning models for pre-microRNA detection
(Walter De Gruyter, 2017)
MicroRNAs (miRNAs) are involved in the post-transcriptional regulation of protein abundance and thus have a great impact on the resulting phenotype. It is, therefore, no wonder that they have been implicated in many diseases ...
Visualization and analysis of microRNAs within KEGG pathways using VANESA
(Walter De Gruyter, 2017)
MicroRNAs (miRNAs) are small RNA molecules which are known to take part in post-transcriptional regulation of gene expression. Here, VANESA, an existing platform for reconstructing, visualizing, and analysis of large ...
AltORFev facilitates the prediction of alternative open reading frames in eukaryotic mRNAs
(Oxford University Press, 2017)
Motivation: Protein synthesis is not a straight forward process and one gene locus can produce many isoforms, for example, by starting mRNA translation from alternative start sites. altORF evaluator (altORFev) predicts ...
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 ...
Newly developed SSR markers reveal genetic diversity and geographical clustering in spinach (Spinacia oleracea)
(Springer, 2017-08)
Spinach is a popular leafy green vegetable due to its nutritional composition. It contains high concentrations of vitamins A, E, C, and K, and folic acid. Development of genetic markers for spinach is important for diversity ...
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 ...
Development of genomic simple sequence repeat markers in faba bean by next-generation sequencing
(Springer, 2017-02)
Faba bean (Vicia faba L.) is an important food legume crop with a huge genome. Development of genetic markers for faba bean is important to study diversity and for molecular breeding. In this study, we used Next Generation ...
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 ...
PGMiner: Complete proteogenomics workflow; from data acquisition to result visualization
(Elsevier, 2017-04)
In parallel with the development of nucleotide sequencing an equally important interest in further describing the sequence in terms of function arose and the latter represents the current bottleneck in the overall research ...
