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A Monte-Carlo Code: Sequential Importance Sampling with Pilot-Exploration Resampling (SISPER) Applied to a 2D Protein Folding

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STAT525-SISPER

Developers:

Zhikun Cai, Chenchao Shou, Guanfeng Gao

Problem:

Searching for the lowest-energy folded state of protein in a 2D hydrophobic-hydrophilic (HP) lattice model

Algorithm:

Sequential Importance Sampling with Pilot-Exploration Resampling (SISPER)

Reference:

J. L. Zhang and J. S. Liu, A new sequential importance sampling method and its application to the two-dimensional hydrophobic-hydrophilic model, Journal of Chemical Physics, 117, 3492 (2002)

Code Usage:

(1) Use sisper.py to run the simulation with a prepared sequence file as input (tau acts like temperature):

    $ cd src
    $ python sisper.py sequence_file_name conformation_file_name tau

(2) Use plot_conformations.py to plot the protein conformation found and save the figures:

    $ python plot_conformations.py sequence_file_name conformation_file_name fig_file_keywords num_of_figs

Example:

See the test folder

    $ cd test
    $ python ../src/sisper.py sequence.txt conformations_tau0.5 0.5
    $ python ../src/plot_conformations.py sequence.txt conformations_tau0.5 plots_tau0.5 8

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A Monte-Carlo Code: Sequential Importance Sampling with Pilot-Exploration Resampling (SISPER) Applied to a 2D Protein Folding

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