Abstract
Abstract: Endogenous small RNAs (miRNA) are the key regulators of numerous eukaryotic lineages playing an important role in a broad range of plant development. Computational analysis of miRNAs facilitates the understanding of miRNA-based regulations in plants. The discovery of small non-coding RNAs has led to a greater understanding of gene regulation, and the development of bioinformatic tools has enabled the identification of microRNAs (miRNAs) and their targets. The need for comprehensive miRNA analysis is being accomplished by the development of advanced computational tools/algorithms and databases. Each resource has its own specificity and limitations for the analysis. This review provides a comprehensive overview of various algorithms used by computational tools, software, and databases for plant miRNA analysis. However, over a period of about two decades, a lot of knowledge has been added to our understanding of the biogenesis and functioning of miRNAs in other plants. Several parameters were already integrated and others need to be incorporated in order to give more accurate and efficient results. The reassessment of computational recourses (based on old algorithms) is required on the basis of new miRNA research and development. Generally, computational methods, including ab-initio and homology search-based methods, are used for miRNA identification and target prediction. This review presents the new challenges faced by the existing computational methods and the need to develop new tools and advanced algorithms and highlight the limitations of existing computational tools and methods, and emphasizing the need for a comprehensive platform for miRNA gene exploration.
Published Version
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