MIMRDA: A Method Incorporating the miRNA and mRNA Expression Profiles for Predicting miRNA-Disease Associations to Identify Key miRNAs (microRNAs)

miRNAs in Heart Development and Disease

Cardiovascular diseases (CVD) are a group of disorders that affect the heart and blood vessels. They include conditions such as myocardial infarction, coronary artery disease, heart failure, arrhythmia, and congenital heart defects. CVDs are the leading cause of death worldwide. Therefore, new medical interventions that aim to prevent, treat, or manage CVDs are of prime importance. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the posttranscriptional level and play important roles in various biological processes, including cardiac development, function, and disease. Moreover, miRNAs can also act as biomarkers and therapeutic targets. In order to identify and characterize miRNAs and their target genes, scientists take advantage of computational tools such as bioinformatic algorithms, which can also assist in analyzing miRNA expression profiles, functions, and interactions in different cardiac conditions. Indeed, the combination of miRNA research and bioinformatic algorithms has opened new avenues for understanding and treating CVDs. In this review, we summarize the current knowledge on the roles of miRNAs in cardiac development and CVDs, discuss the challenges and opportunities, and provide some examples of recent bioinformatics for miRNA research in cardiovascular biology and medicine.

A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective

Molecular and sequencing technologies have been successfully used in decoding biological mechanisms of various diseases. As revealed by many novel discoveries, the role of non-coding RNAs (ncRNAs) in understanding disease mechanisms is becoming increasingly important. Since ncRNAs primarily act as regulators of transcription, associating ncRNAs with diseases involves multiple inference steps. Leveraging the fast-accumulating high-throughput screening results, a number of computational models predicting ncRNA-disease associations have been developed. These tools suggest novel disease-related biomarkers or therapeutic targetable ncRNAs, contributing to the realization of precision medicine. In this survey, we first introduce the biological roles of different ncRNAs and summarize the databases containing ncRNA-disease associations. Then, we suggest a new trend in recent computational prediction of ncRNA-disease association, which is the mode of action (MoA) network perspective. This perspective includes integrating ncRNAs with mRNA, pathway and phenotype information. In the next section, we describe computational methodologies widely used in this research domain. Existing computational studies are then summarized in terms of their coverage of the MoA network. Lastly, we discuss the potential applications and future roles of the MoA network in terms of integrating biological mechanisms for ncRNA-disease associations.