The performances of the chi-square test and complexity measures for signal recognition in biological sequences

Signal detection in genome sequences using complexity based features

“…The application of statistical methods such as Pearson's chi-square test to detect the signals in the whole genome of the Escherichia coli is presented in [12]. The efficiency of the method is evaluated by comparing the Pearson's chisquare test with linguistic, CE and CWF complexity on the complete genome of E. coli.…”

“…The longest sequence without a stop codon usually determines the ORF. In our work, we simply use this rule (which was used in [12]) to identify ORFs in the genome sequences of three prokaryotic organisms. Note that this simple method is not applicable to eukaryotes.…”

“…These positions are the start codon position, the middle of the ORF and the stop codon position. Since authors in [12] showed that the region near the start codon has the best performance in discriminating genes from pseudo-genes, we concentrate on this position in this work. However, considering the region near the start codon position, there are three areas to study.…”

“…These techniques can be used to recognize specific regions with particular structures and specific functions in a long sequence. For example, they can be used to analyze phylogenetic networks, discriminating coding, non-coding and regulatory regions and recognizing repeated sequences [12,15,3,2].…”

“…Recently, it has been shown that the area around the start codon position of ORFs has the best performance for discriminating genes from pseudo-genes among other positions of an ORF [12]. Thus, we only consider this specific region of ORFs for our discriminating test.…”