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A new system, ZCURVE 1. 0, for finding protein- coding genes in bacterial and archaeal genomes has been proposed. The current algorithm, which is based on the Z curve representation of the DNA sequences, lays stress on the global statistical features of protein-coding genes by taking the frequencies of bases at three codon positions into account. In ZCURVE 1. 0, since only 33 parameters are used to characterize the coding sequences, it gives better consideration to both typical and atypical cases, whereas in Markov-model-based methods, e. g. Glimmer 2. 02, thousands of parameters are trained, which may result in less adaptability. To compare the performance of the new system with that of Glimmer 2. 02, both systems were run, respectively, for 18 genomes not annotated by the Glimmer system. Comparisons were also performed for predicting some function-known genes by both systems. Consequently, the average accuracy of both systems is well matched; however, ZCURVE 1. 0 has more accurate gene start prediction, lower additional prediction rate and higher accuracy for the prediction of horizontally transferred genes. It is shown that the joint applications of both systems greatly improve gene-finding results. For a typical genome, e. g. Escherichia coli, the system ZCURVE 1. 0 takes approximately 2 min on a Pentium III 866 PC without any human intervention. The system ZCURVE 1. 0 is freely available at: http: //tubic. tju. edu. cn/ZcurveB/.
Feng‐Biao Guo (Fri,) studied this question.