Abstract
Latest discoveries support the synergistic and antagonist role of transcription factors (TFs) and microRNAs (miRNAs) in the messenger RNA (mRNA) regulation. The mutual interactions among these molecules have been modeled and analyzed through graphs where nodes are molecules, including TF, miRNAs and mRNA product and edges represent the directed associations among them. A particular small subgraphs have three nodes and also referred as feed-forward loops (FFLs) or regulatory loops, that play a crucial role in different diseases, including cancer. Available technological platforms allow the investigation of only a single aspect of these mechanisms, for example, the quantification of levels of mRNA or miRNA. Consequently, there exist different data sources that starting from this information investigate some aspects of this problem, for example miRNA-mRNA or TF-mRNA associations. The comprehensive analysis is possible only by the integration and the analysis performed by the use of these data sources. Currently, the interest of researchers in this area is growing, the number of projects is increasing, and the number of challenges and issues for computer scientists arises. This article starts by discussing general concepts related to production of data. Then, main existing approaches of analysis are presented and discussed. Future improvements and challenges will also discussed.
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