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ABSTRACT

The realm of long non-coding RNAs (lncRNAs) is experiencing rapid growth, through an increasing number of newly identified transcripts annually. To enhance the precise identification of lncRNAs within the vast pool of genomic data, machine learning-based bioinformatics tools prove indispensable. The utilization of machine learning-based tools for lncRNA prediction in research has gained prominence in recent years. These advanced computational methods offer a powerful means to discern potential lncRNA candidates within vast genomic datasets, enhancing our understanding of their roles in various biological processes. Here, we provide the significance of employing machine learning techniques in lncRNA prediction, datasets, and features importance, showcasing their capacity to accelerate and refine genomic research endeavors. These tools offer researchers powerful solutions to shift through genomic data, aiding in the discovery and functional characterization of lncRNAs, ultimately advancing our understanding of their roles in biological systems.

Keywords: Machine learning; lncRNAs; Genomic data; Bioinformatics; Biological systems

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Prediction of lncRNAs using machine learning-based tools_compressed.pdf