FPGA-based hardware accelerator for the prediction of protein secondary class via fuzzy K-nearest neighbors with LempelZiv complexity based distance measure
Fuzzy KNN with Complexity-based Distance Measure algorithm is proposed. We model the algorithm using FPGA device on Z277 and 25PDB datasets. Parallel processing capability of FPGA is used to improve the prediction speed. Approximately 15 times faster computation speed can be achieved. The algorithm is more effective for high sequence homology protein dataset.
protein secondary structure prediction protein structural class lempelziv algorithm k-nn classification algorithm fuzzy k-nearest-neighbor algorithm field programmable gate arrays