Algorithm Optimization of Minimum Free Energy- Based Amino Acid Sequence Permutation Using OpenCL

Computationally complex algorithms are very useful when attempting to accurately predict the secondary structure of RNA. This paper seeks to use rule-based permutation with OpenCL to output every possible RNA sequence that fits a particular protein amino acid sequence (rule).In previous research, two algorithms were explored along with their possible application in the field of bioinformatics and biochemical engineering. One of these two algorithms is further optimized using OpenCL, a cross platform programming language known for its parallel computing potential and its ability to leverage processing power of GPU's and like devices. We propose that improving RNA secondary structure prediction accuracy can be achieved by extensive analysis of natural occurring RNA folds in comparison to others like them that belong to the same Amino acid sequence.