Abstract

Current Challenges of Computational Intelligent Techniques for Functional Annotation of ncRNA Genes

The limited understanding of functional annotation of non-coding RNAs (ncRNAs) has been largely due to the complex functionalities of ncRNAs. They perform a vital part in the operation of the cell. There are many ncRNAs available such as micro RNAs or long non-coding RNAs that play important functions in the cell. In practice, there is a strong binding of the function of RNAs that must be considered to develop computational intelligent techniques. Comprehensive modeling of the structure of an ncRNA is essential that may provide the first clue towards an understanding of its functions. Many computational techniques have been developed to predict ncRNAs structures but few of them focused on the functions of ncRNA genes. Nevertheless, the accuracy of the functional annotation of ncRNAs is still facing computational challenges and results are not satisfactory. Here, many computational intelligent methods were described in this paper to predict the functional annotation of ncRNAs. The current literature review is suggested that there is still a dire need to develop advanced computational techniques for functional annotating of ncRNA genes in terms of accuracy and computational time.

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