ExSep: An exon separation process using Neural Skyline Filter

Abstract

Exons and Introns are complimentary parts of DNA and RNA. Due to excessive data set in biological science, it is sometimes very expensive and costly to extract meaningful information from such data set. To accelerate efficient and faster exons separation an automated system designed under Neural Skyline Filter(NeuralSF) and Bloom filter. This development allows the comparative analysis on performances among NeuralSF, Bloom Filter and processing without filter. The outcome of the experiments and simulations shows that NeuralSF outperforms other processes in both the cases as number of exons finding and timing. This system may help to reduce the redundant data set from large number of collections. Apart from that it will enable to handle big biological data.