1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Quantitative analysis for identifying important disease-related microRNAs
Paper ID : 1388-ICB10
Authors:
Alborz Esfandyari *1, Hossein Hajnorouzi1, Zeinab Zali2
1دانشجو کارشناسی ارشد مهندسی کامپیوتر- نرم افزار دانشگاه صنعتی اصفهان
2استاد دانشگاه صنعتی اصفهان
Abstract:
Irregularities in gene expression, and therefore, overproduction or underproduction of essential proteins, are the key reasons for the development of various diseases. Lately, one of the treatment methods that researchers are exploring is to investigate the regulatory mechanisms of gene expression. MicroRNAs are one of these regulatory factors [1] that bind to the genes in specific regions called the binding sites [2] and prevent the expression of proteins. As a result, if microRNAs fail to execute their function, protein production will be out of the normal range.
Studying the microRNAs involved in a disease can potentially lead to finding a cure for that disease; however, finding the relevant microRNAs is very complex since one microRNA can target multiple genes, and on the other hand, one particular gene can be regulated by multiple microRNAs [3]. Therefore, identifying disease-related microRNAs requires extensive experiments and takes a deal of time and resources. The purpose of this study is to facilitate the work of researchers by ranking the disease-related microRNAs based on their importance in disease. The approach of this study consists of 1) mining the well-established disease-gene [4] and microRNA-target [3] association databases; 2) counting the number of disease-associated genes that are targeted by each microRNA; and 3) calculating the proportion of disease-associated microRNA targets relative to all of the predicted targets of each microRNA.
Finally, according to the timeliness, the proposed approach of this study has been applied to three diseases, coronavirus, covid-19, and B.1.1.7 [3-6]. This approach resulted in the identification of hsa-miR-548c-3p and hsa-miR-551a as the most important microRNA associated with coronavirus, hsa-miR-652-3p and hsa-miR-548c-3p associated with covid-19 and hsa-miR-423-5p and hsa-miR-4446-3p associated with B.1.1.7.
Keywords:
MicroRNAs; Gene expression; Protein; Counting; Coronavirus.
Status : Paper Accepted (Poster Presentation)