Recognition of gene promoters in human beings based on the particle swarm optimized support vector machine algorithm
Recognition of gene promoters in human beings is a basic requirement for medical research. It was achieved through analysis of phase-specific PZ curves of nucleotide, spatial structure of nucleotide, conservative signal and K-mer likelihood score in DNA sequence, as well as GC content changes and in-homogeneity index. The support vector machine algorithm based-particle swarm optimization was proposed to identify human gene promoters. Using PSO algorithm to optimize the parameters of SVM can avoid the randomness of artificial selection and present better robustness in classification. The sensitivity, specificity and MCC tested by the 10-fold cross-validation were 92%, 91%, and 0.83, respectively. The result indicated that PSO-SVM method can be used to effectively identify promoter sequences.