Polymorphic BCO for protein folding model

Yudong Zhang*, Yuankai Huo, Qing Zhu, Shuihua Wang, Lenan Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


To improve the protein folding simulations, polymorphic bacterial chemotaxis optimization (PBCO) was investigated on a 2D lattice model. PBCO is a novel intelligent problem solving technique inspired from the foraging behavior of bacteria. We compared PBCO with standard genetic algorithm (SGA) and Immune Genetic Algorithm (IGA) for various chain lengths. It shows that PBCO has the highest successful rate and the lowest computation time.

Original languageEnglish
Pages (from-to)1787-1794
Number of pages8
JournalJournal of Computational Information Systems
Issue number6
Publication statusPublished - Jun 2010
Externally publishedYes


  • Immune genetic algorithm
  • Polymorphic bacterial chemotaxis optimization
  • Protein folding model
  • Standard genetic algorithm


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