CHEN Yang and WANG Shoujue. “Comparing the Performance of BiomimeticPattern Recognition with W8 and SVM onPrediction of Horizontal Gene Transfers inBacteria Genomes”. Chinese Journal of Electronics, vol. 19 no. 1.
Citation:
CHEN Yang and WANG Shoujue. “Comparing the Performance of BiomimeticPattern Recognition with W8 and SVM onPrediction of Horizontal Gene Transfers inBacteria Genomes”. Chinese Journal of Electronics, vol. 19 no. 1.
CHEN Yang and WANG Shoujue. “Comparing the Performance of BiomimeticPattern Recognition with W8 and SVM onPrediction of Horizontal Gene Transfers inBacteria Genomes”. Chinese Journal of Electronics, vol. 19 no. 1.
Citation:
CHEN Yang and WANG Shoujue. “Comparing the Performance of BiomimeticPattern Recognition with W8 and SVM onPrediction of Horizontal Gene Transfers inBacteria Genomes”. Chinese Journal of Electronics, vol. 19 no. 1.
With the accomplishment of sequencing genomes, lots of homologous genes had been found in dif- ferent species. These homologous genes are called horizon- tal transfer genes, in which genetic material is transferred from the genome of one organism to another. Prediction of the Horizontal gene transfers (HGT) has important mean- ing for understanding the genome evolution and estimating the hereditary material between species. A novel approach based on Biomimetic pattern recognition (BPR) was pro- posed to predict the horizontal gene transfers in bacte- rial genomes. The basis of BPR points to the Principle of homology-continuity (PHC) that the di®erence between two samples of the same class must be gradually changed. The aim of BPR is to ¯nd an optimal covering in the fea- ture space, which rather than \division" in traditional pat- tern recognition, emphasizing the \similarity" among ho- mologous group members. Two neuron models called Hy- per sausage neuron (HSN) and Ã3-neuron as covering units in BPR were used to construct the multi-weighted neural network. The performance of the approach was superior to that of gene scoring method of 8-nucleotide composition (W8) and one-class Support vector machine (SVM).
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