TY  - RPRT
ID  - SisLab2894
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2894/
A1  - Do, Duc Dong
Y1  - 2017///
N2  - 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.
PB  - VNU-UET Technical Report
VL  - TR2017-FIT-002
M1  - technical_report
TI  - A Novel and Efficient Ant Colony Optimization Algorithm for Protein 3D Structure Prediction
AV  - public
EP  - 7
ER  -