Release Time:2019-03-11  Hits:

Indexed by: Conference Paper

Date of Publication: 2009-03-30

Included Journals: Scopus、CPCI-S、EI

Page Number: 114-120

Abstract: Many species of Gram-negative bacteria are pathogenic bacteria that can cause disease in a host organism. This pathogenic capability is usually associated with certain components in Gram-negative cells, so it is highly desirable to develop an effective method to predict the Gram-negative bacterial protein subcellular locations. Reflecting the wide applications of neural networks in this field, we design seven different training functions based on Elman networks, and use a genetic algorithm to select the proper networks for an ensemble. Experimental results show that the neural networks ensemble has a dominant advantage in performance.