Comparative Analysis of miRNA-Target Prediction Algorithms with Experimentally Positive Data in C. elegans and R. norvegicus Genomes
| Autor: | Debabrata Mandal, Uttam Roy Mandal, Shibsankar Das |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Computational biology Biology Positive data complementarity score Applied Microbiology and Biotechnology Microbiology Genome QR1-502 Mirna target 03 medical and health sciences Prediction algorithms 030104 developmental biology target validation computational methods mirna - mrna target interactions Biotechnology |
| Zdroj: | Journal of Pure and Applied Microbiology, Vol 12, Iss 1, Pp 361-368 (2018) |
| ISSN: | 0973-7510 |
| DOI: | 10.22207/jpam.12.1.42 |
| Popis: | MicroRNAs (miRNAs) are small non-encoding RNAs of 19-24 nucleotides long. It regulates gene expression through target mRNA degradation or translational gene silencing. Experimental based prediction is laborious and economically unfavorable due to a huge number of miRNAs and potential targets. So researchers are focused on computational approach for faster prediction. A large number of computational based prediction tools have been developed, but their results are often inconsistent. Hence, finding a reliable computational based prediction tool is still a challenging task. Here we proposed a computational method, microTarget for finding miRNA - mRNA target interactions. We validated our result in C. elegans and Rattus norvegicus genomes and compared performance with three computational methods, like miRanda, PITA, and RNAhybrid. Signal-to-noise ratio, z score, Receiver operating characteristic (ROC) curve analysis, Matthews correlation coefficient (MCC) and F measure show that microTarget exhibits good performance than other three miRNA - mRNA target interactions methods used in this study. |
| Databáze: | OpenAIRE |
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