1. POA Simulation
MEC Seminar
임희웅

2. Contents Introduction Algorithm and Workflow
Architecture and Environment
Result
Discussion
Reference

3. Introduction Lee et al. DNA10, 2004 Inside of POA
Prediction of experimental result without real experiment
23 city TSP
Information for experimental setup

4. Algorithm and Workflow
Simplified version of Maheshri et al.(2003)
Random selection and collision model
Selection with a probability proportional to the number of corresponding DNA. (roulette-wheel selection)
Annealing event probability by Gibbs free energy and NN model
No gapped annealing or bulge
Consider only match sections
Sum of all the free energy in match sections
Boltzmann-weighted probability for each annealing event

5. Workflow

6. Architecture and Environment

7. Result (1) Cycle 10 Cycle 20 Cycle 30 Cycle 6 Cycle 5 Cycle 1 Cycle2

8. Result (2)
100
200
300

9. Discussion Fidelity of POA? Annealing temperature Validity of NN model
Low extension efficiency in later cycle
Unextendable hybridization
Annealing temperature
Annealing temperature gradient? (low  high)
Validity of NN model

10. Reference
J. Santalucia, Jr. A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbor thermodynamics, PNAS, 1998
N. Maheshri, et al. Computational and experimental analysis of DNA shuffling, PNAS, 2003, and its supplement
J. Y. Lee, et al Efficient initial pool generation for weighted graph problems using parallel overlap assembly, DNA10, 2004