Maryam Koraei - Department of Biological Science, Faculty of Science, University of Kurdistan, Sanandaj, Iran
Aso Mafakheri - Department of Computer Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
Shamseddin Ahmadi - Department of Biological Science, Faculty of Science, University of Kurdistan, Sanandaj, Iran
Sadegh Sulaimany - Department of Computer Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

MicroRNAs are small non-coding RNAs with a pivotal role in morphine addiction and tolerance. However,little is known about specific microRNAs involved in regulating molecular mechanisms of addiction.Therefore, the identification of microRNAs targeting specific genes involved in addiction throughcomputational methods could be very helpful in reducing the time and cost of laboratory methods. The aimof this study is to investigate the possible connections between microRNAs and genes involved in morphineaddiction in rats by using bioinformatics tools. In this way, high probable communications that will be usefulfor purposeful future laboratory studies will be identified and proposed.First, a list of microRNAs and genes involved in morphine addiction was collected by searching in NCBIdatabase and ۳۰ microRNAs and ۱۴۴ related genes were selected. Then, links between the genes and themicroRNAs involved in morphine addiction in rats were found using MicroRNA Target Prediction Database(www.mirdb.org). Thereafter, the desired connections were modeled in the form of a bipartite network, therelationships between microRNA and genes was graphed, and then a customized version of link predictionalgorithms was set to find the most probable relations between the related microRNAs and target genes.Further, the accuracy of the results was calculated and confirmed by measuring the AUC.Finally, the ۲۰ top relations predicted were reported in order of priority. new relation between rno-miR-۱-۳p,rno-miR-۱b, rno-miR-۹a-۵b, rno-miR-۱۶-۵p, rno-miR-۲۷a-۳p, rno-miR-۱۳۲-۳p, rno-miR-۱۹b-۳p and rnomiR-۲۱۲-۳p recpectively with Ms۴a۷, Pi۴ka, Creb۱, Avpr۱a, Cxcr۵, Slain۲, Creb۱ and Tdrd۷ are predicted.These computational findings are the most promising connections that are likely to exist but have not yetbeen reported in the online databases. They are the best choices to be validated using in vitro studies.Therefore, a proposed way is to perform related laboratory tests to confirm or disprove such predictions.

Morphine, Addiction, microRNA, Target gene, Link prediction, Rat