Taxonomy process for RNA motif discovery

A motif is a small part of DNA or RNA sequence which has the constant size and related to the DNA and RNA functions [1]. Recently discovered non-coding RNAs especially microRNAs with regulatory functions has opened a new research area [2-5]. Finding the motif pattern and function provide an attractive research path for bioinformaticists [6]. Many algorithms have been devised to solve the RNA motif discovery problem, nevertheless, due to the lack of a standard benchmark, quantitative work needed to evaluate their performance. Accordingly, the aim of the current study were to present a taxonomy for the motif discovery process in RNA. This taxonomy provides a systematic way to the RNA motif discovery problem which includes 4 dimensions: 1) approaches and algorithms that have been used to identify and predict motifs in RNA molecule; 2) information which is used as inputs of algorithms and tools; 3) active agents involved in the motif discovery in RNA; and 4) the application of RNA motifs in different fields. Studying each dimensions helps to get a better insight of the motif discovery process in RNA and presents a complete and comprehensive category which enhances the speed of access to motif discovery algorithms and tools.

کلیدواژه ها:

micro RNA ، Motif finding ، computer algorithms ، bioinformatics