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Solutions of Shortest Path Problems by Concentration Control

Learn about solving shortest path problems through concentration control methods, using DNA concentrations as input/output data. Reduce costs via local search optimization. Explore algorithms, encoding, random path construction, and more. Simulation and lab experiments show results of gel analysis for quantification and identification.

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Solutions of Shortest Path Problems by Concentration Control

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  1. Solutions of Shortest Path Problems by Concentration Control N. Matsuura et al. DNA7, 2001 Summarized by Shin, Soo-Yong

  2. Concentration control • Solve shortest path problem by concentration control methods. • The concentrations of DNA are used as input and output data. • By local search rather than exhaustive search. • We can reduce the costs of some experimental operations. (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  3. Shortest path problems (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  4. Algorithms • Encoding • Construction of random path • Same as Adleman method • Relative concentration • PCR • Determination by SSCP (Single Stranded Conformation Polymorphism). • Or DGGE, TGGE (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  5. Simulation Experiments • Without and with concentration control Solution (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  6. Lab experiments • Similar with Adleman experiments (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  7. Results of Gel Analysis (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  8. Results of Gel Analysis (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  9. Quantification & Identification (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

  10. Quantification & Identification (C) 2001, SNU Biointelligence Lab, http://bi.snu.ac.kr/

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