Performance comparison of techniques for DNA sequence prediction using neural networks

The conversion of symbolic sequences into complex genomic signals reveals surprising regularities of genomes, both locally and at a global scale. This approach allows usage of standard signal processing methods for the nucleotide sequences analysis and specifically for the prediction of nucleotides when knowing the preceding ones in a sequence. In this paper we propose variety of methods and ways when using artificial neural networks at its core to efficiently predict the next sample in the genomic sequence.