1. Blueprint for NACST/Sim 2002.10.25 신수용

2. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Main concept Implementing Hybridization first. Then, ligation, PCR, and so on..  Can be implemented easily based on hybridization concept. 그외..  Gel electrophoresis is easy.  Bead seperation 은 아직 고려하지 않음

3. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Main concept Probabilistic model! Sequence Collision Probability  Tube 에서 sequence 들이 어떻게 분포하고 있으며, 어떤 sequence 들이 서로 만날 것인가에 대한 모델 Sequence Hybridization Probability  서로 만난 sequence 들의 결합가능성 판단

4. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Collision model Based on Artificial Chemistry  Artificial Chemistries: A Review, P. Dittrich, J. Ziegler, and W. Banzhaf  Multi-Agent Systems inspired by Artificial Chemistries: A Case Study in Automated Theorem Proving, J. Bush and W. Banzhaf

5. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Collision model (AC) 현재의 DNAC 를 위해서는 초기에 입력은 전부 주어지며, 출력도 없는 단순한 모델로 충분. Sequence 들은 uniform distribution 에 근거하 여 확률적으로 선택됨 Hybridization 이 되어 긴 sequence 가 새로 생 기면 추가적인 input 으로 가정

6. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Hybridization model Based on Sequence Alignment Algorithms Dynamic Programming!  Smith-Waterman Algorithm(?)  좀 더 빠른 알고리즘을 원함.!  독일에서 만든 알고리즘은 시퀀스 2 개 주고 결과를 얻기 위해서는 대략 5-9 초 정도의 시간이 필요.  DNASIM: 1998, Jens Niehaus Blast 도 동일한 알고리즘을 사용

7. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Hybridization model (DP) Biological sequence analysis: Probabilistic models of proteins and nucleic acids, R. Dublin, S. R. Eddy, A. Krogh, and G. Mitchison Introduction to Algorithms, T. H. Cormen, C. E. Leiserson, and R. L. Rivest

8. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Hybridization model (DP) Sequence matching table(?) 이 중요.

9. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor model for Tm R : Boltzmann’s constant (1.987 cal/(K mol)) [C ] ] : total molar strand concentration T : Kelvin [Na + ] concentrations different from 1M

10. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor model for Tm Self-complement : [C T ]/4  [C T ]/2 The strands are not in equimolar concentration, but one strand is present in gross excess over the other : [C T ]/4  [C T ] mismatched base pairs : “virtual stacks” (see references)

11. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : Perfect WC basepairing

12. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Example GCTAGC at 0.1mM  H = 2(-11.1) + 2(-6.1) + (-6.3) = -40.7 kcal/mol  S = 2(-28.4) + 2(-16.1) + (-18.5) – 5.9 –1.4 = -114.8eu

13. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : GT mismatch Thermodynamics and NMR of Internal G.T Mismatches in DNA, H. T. Allawi and J. SantaLucia, Jr., Biochemistry 1997, 36, 10581- 10594

14. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : GT mismatch

15. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : GA mismatch Nearest Neighbor Thermodynamic Parameters for Internal GA Mismatches in DNA, H. T. Allawi, J. SantaLucia, Jr., Biochemistry 1998, 37, 2170-2179

16. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : GA mismatch

17. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : CT mismatch Thermodynamics of internal CT mismatches in DNA, H. T. Allawi and J. SantaLucia, Jr., Nucleic Acids Research, 1998, 26(11): 2694- 2701

18. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : CT mismatch

19. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : AC mismatch Nearest-Neighbor Thermodynamics of Internal AC Mismatches in DNA: Sequence Dependence and pH Effects, H. T. Allawi and J. SantaLucia, Jr., Biochemistry, 1998, 37, 9435- 9444

20. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : AC mismatch

21. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : AA, CC, GG, and TT mismatch Nearest-Neighbor Thermodynamics and NMR of DNA sequences with Internal AA, CC, GG, and TT Mismatches, N. Peyret, P. A. Senevirante, H. T. Allawi, and J. SantaLucia, Jr., Biochemistry 1999, 38, 3468-3477

22. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : AA, CC, GG, and TT mismatch

23. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : Single base bulge The Effect of Base Sequence on the Stability of RNA and DNA Single Base Bulges, J. Zhu and R. M. Wartell, Biochemistry 1999, 38, 15986-15993

24. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : Single base bulge

25. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : Hairpin Melting Studies of Short DNA Hairpins: Influence of Loop Sequence and Adjoining Base Pair Identity on Hairpin Thermodynamic Stability, P. M. Vallone, T. M. Paner, and J. Hilario, M. J. Lane, B. D. Faldasz, and A. S. Benight, Biopolymers, 50, 425-442 (1999)

26. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/

27. Nearest-neighbor data : Dangling ends Thermodynamic parameters for DNA sequences with dangling ends, S. Bommarito, N. Peyret, and J. SantaLucia, Jr., Nucleic Acids Research, 2000, 28(9): 1929-1934

28. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Nearest-neighbor data : Dangling ends

29. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ Etc Ionic condition…  Differences between DNA Base Pair Stacking Energies Are Conserved over a Wide Range of Ionic Conditions, T. Johnson, J, Zhu, and R. M. Wartell, Biochemistry 1998, 37, 12343-12350

30. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ For implementation We need to know  HOW MANY MOLECULES ARE NECESSARY?  HOW MUCH TIME IS NECESSARY?

31. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ HOW MANY MOLECULES ARE NECESSARY? (V) i.e. v1, v2, v3, v4, e1, e2, e3  e1 : v1->v2, e2 : v2->v3, e3 : v3->v4 1. v1, v2, e1 -> p1 2. p1, v3, e2 -> p2

32. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ HOW MANY MOLECULES ARE NECESSARY? (V) 3. p2, v4, e3 -> p3 … 적정한 양 ?

33. © 2002, SNU BioIntelligence Lab, http://bi.snu.ac.kr/ HOW MUCH TIME IS NECESSARY? (x)