@techreport{SisLab2894,
          number = {TR2017-FIT-002},
            type = {Technical Report},
           title = {A Novel and Efficient Ant Colony Optimization Algorithm for Protein 3D Structure Prediction},
          author = {Duc Dong Do},
       publisher = {VNU-UET Technical Report},
            year = {2017},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2894/},
        abstract = {Protein structure prediction (PSP) is considered as one of the most long-standing and challenging problem in bioinformatic. In this paper, we present an efficient ant
colony optimization algorithm to predict the protein structure on three-dimensional face-centered cubic lattice coordinates, using hydrophobic-polar (HP) model and MiyazawaJernigan (MJ) model to calculate the free energy. The reinforcement learning information is expressed in the k-order Markov model, the heuristic information is determined based on the increase of the
total energy. On a set of benchmark proteins, the results show a remarkable efficiency of our algorithm by comparing with the state-of-the-art algorithms.}
}