Artificial immune system for protein folding model

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


To improve protein folding simulations, artificial immune system (AIS) was investigated on a 2D lattice model. AIS is a novel intelligent problem solving technique inspired from vertebrate immune system. Compared with stand genetic algorithm (SGA), AIS contains four new operators such as cloning selection, inverse mutation, pair wise interchange mutation, and receptor editing. In the experiments, we compared AIS with the immune genetic algorithm (IGA) for 4 chains of different lengths of 20, 36, 48, and 64. The results show that AIS has a higher success rate but costs more time.

Original languageEnglish
Pages (from-to)55-61
Number of pages7
JournalJournal of Convergence Information Technology
Issue number1
Publication statusPublished - Jan 2011
Externally publishedYes


  • Artificial immune system
  • Immune genetic algorithm
  • Protein folding model


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