Description
RNA, once considered to be just a carrier of genetic information, is now known to play a broader role in nature. In many RNA-related studies, knowing the secondary structure of an RNA sequence reveals important constraints governing the molecule's physical properties and function. Experimental determination of RNA structure remains difficult. For predicting secondary structure of RNA molecules, many software packages are currently in use which use different approaches to predict RNA secondary structure. No standardization exists for ranking or comparing these prediction algorithms. Also no benchmark dataset exists to be used for comparison. As a result it is difficult to compare a new prediction algorithm with existing algorithms. To overcome this problem of evaluating performance of different algorithms, we try to get results from major prediction software based on a wide variety of RNA sequences obtained from RNA STRAND as input, and compare the results on the basis of some standard comparison parameters. Also in our research we choose a method which gives the best overall prediction results compared to other methods, and we try to come up with an algorithm which can help the user to determine a method's accuracy of a secondary structure prediction.
