@article{1027,
  author = {A. Boukra, S. Bouroubi},
  title = {Protein Structure Prediction Using Honey-Bee Mating Optimization},
  journal = {Journal of Intelligent Computing},
  year = {2012},
  volume = {3},
  number = {3},
  doi = {},
  url = {http://www.dline.info/jic/fulltext/v3n3/2.pdf},
  abstract = {Protein folding prediction is a fundamental problem in biology. The spatial structure (Conformation) of the protein is the manipulation key of its biochemical and cellular functions. The protein tends to fold on itself. However, a protein cannot fold in any way: it must reach a lowest level of energy. Determining the conformation of the protein in this state of lowest energy is known as the protein folding problem. This can be modeled as an optimization problem. Even under the simplified models, the problem is NP-complete [1] [2] [3]. Thus, there is no polynomial time algorithm to resolve this problem. In this paper, a biologically inspired algorithm for protein spatial structure prediction is proposed; it uses the honey-bee colony reproduction processes.},
}