POA Simulation 2004.5.25 MEC Seminar 임희웅

Contents Introduction Algorithm and Workflow Architecture and Environment Result Discussion Reference

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

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

Workflow

Architecture and Environment

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

Result (2) 100 200 300

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

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