2. Who am I?

3. namedanny van noort educationMSc. experimental physics university of Leiden The Netherlands PhD. applied physics Linköpings university Sweden Post docsBioMIP (BioMolecular Information Processing) Institute of computer science and mathematics (GMD) Sankt Augustin Germany Dept. of Ecology and Evolutionary Biology Princeton University USA Who am I?

4. namedanny van noort OfficeRoom 410 buildingRIACT tel:None yet emaildanny@bi.snu.ac.kr webhttp://bi.snu.ac.kr/ Where to find me

7. Course outline

8. 1Introduction 2Theoretical background  Biochemistry/molecular biology  Computation 3Extension of theoretical background (biochemistry or computer science) 4History of the field 5Splicing systems 6P systems 7Hairpins 8Micro technology introductions Microreactors / Chips 9Microchips and fluidics 10Self assembly 11Regulatory networks 12Molecular motors 13DNA nanowires 14DNA computing - summery Course outline

9.  Essay on new molecular computing idea  Presentation  and/or setting up a detailed webpage

10. What is DNA computing?

11. What is DNA Computing?  The field of DNA computing is concerned with the possibility of performing computations using biological molecules.  It is also concerned with understanding how complex biological molecules process information in an attempt to gain insight into new models of computation.  Cells and nature compute by reading and rewriting DNA by processes that modify sequence at the DNA or RNA level. DNA computing is interested in applying computer science methods and models to understand such biological phenomena and gain insight into early molecular evolution and the original of biological information processing.

12. Molecular electronics, Theoretical biology, Evolutionary biology, Emergent computation, Brain sciences, Organic chemistry, Biomimetic engineering, Parallel processing, Distributed computing, Behavioural ecology, Cytology, Discrete mathematics, Optimisation theory, Artificial Intelligence, Cognitive science, Botany, Psychology, Algorithmics, Clinical engineering, Biophysics, Connectionism, Integrative physiology, Technology transfer, Selectionism, Immunology, Automata theory, Evolutionary computation, Simulation of computational systems, Histology, Ethology, Medical computing, Signal transduction and processing, Cellular automata, Electronic engineering, Vision, Object oriented design, Philosophy of science, VLSI, Non-linear dynamical systems, Game theory, Communication, Bioengineering, Self-organisation, Biochemistry, Pattern recognition, Information theory, Machine learning, Biosystem simulation, Genetics, Mathematical biology, Microbiology, Zoology, Science education, Physiology, Systems theory, Biosensors, Analogue devices and sensors, Microtechnology, Robotics... What is DNA Computing?

13. Molecular electronics, Theoretical biology, Evolutionary biology, Emergent computation, Brain sciences, Organic chemistry, Biomimetic engineering, Parallel processing, Distributed computing, Behavioural ecology, Cytology, Discrete mathematics, Optimisation theory, Artificial Intelligence, Cognitive science, Botany, Psychology, Algorithmics, Clinical engineering, Biophysics, Connectionism, Integrative physiology, Technology transfer, Selectionism, Immunology, Automata theory, Evolutionary computation, Simulation of computational systems, Histology, Ethology, Medical computing, Signal transduction and processing, Cellular automata, Electronic engineering, Vision, Object oriented design, Philosophy of science, VLSI, Non-linear dynamical systems, Game theory, Communication, Bioengineering, Self-organisation, Biochemistry, Pattern recognition, Information theory, Machine learning, Biosystem simulation, Genetics, Mathematical biology, Microbiology, Zoology, Science education, Physiology, Systems theory, Biosensors, Analogue devices and sensors, Microtechnology, Robotics... What is DNA Computing?

14. 14 011001101010001ATGCTCGAAGCT What is DNA Computing?

15.  a completely new method among a few others (e.g., quantum computing) of general computation alternative to electronic/semi-conductor technology  uses biochemical processes based on DNA

16. What is DNA Computing not?  not to confuse with bio-computing which applies biological laws (evolution, selection) to computer algorithm design.

17. Biocomputing vs. Bioinformatics Biomolecular computing DNA computing

18. 1.6-2.2 Inter-metal Dielectric K 45 nm 16 Known CMOS limitations 1999 200220052008 2011 <1.5 Source: Texas Instruments and ITRS IC Design Technology Working Group 140 nm 80 nm 60 nm parameters approach molecule size Gate length 4.0 2.7 1.6-2.2 0.25 1 4 Relative Fab Cost

19. 19 Future technology Source: Motorola, Inc, 2000 Now +2+4+6+8+10+12 Full motion mobile video/office Metal gates, Hi-k/metal oxides, Lo-k with Cu, SOI Pervasive voice recognition, “smart” transportation Vertical/3D CMOS, Micro-wireless nets, Integrated optics Smart lab-on-chip, plastic/printed ICs, self-assembly Quantum computer, molecular electronics Bio-electric computers Wearable communications, wireless remote medicine, ‘hardware over internet’ ! 1e6-1e7 x lower power for lifetime batteries True neural computing

20. Historical timeline Research 1950’s … R.Feynman’s paper on sub microscopic computers 1994 L.Adleman solves Hamiltonian path problem using DNA. Field started 1995 D.Boneh paper on breaking DES with DNA Commercial 1970’s … DNA used in bio application 1996 Human Genome Sequence 2000 DNA computer architecture ? Affymetrix sells GeneChip DNA analyzer 2015 Commercial computer ? 2005 Lucent builds DNA “motor”

21. DNA computers vs. conventional computers DNA-based computersMicrochip-based computers slow at individual operations fast at individual operations can do billions of operations simultaneously can do substantially fewer operations simultaneously can provide huge memory in small space smaller memory setting up a problem may involve considerable preparations setting up only requires keyboard input DNA is sensitive to chemical deterioration electronic data are vulnerable but can be backed up easily

22. Computer speed  number of parallel processors  number of steps each processor can perform per unit of time DNA computer  3 grams of water contains 10 22 molecules  massively parallel Electronic computer  advantage in number of steps performed per unit of time Speed of DNA computing

23. information per space unit perform per unit of time DNA computer  10 6 Gbits per cm 2 (1 bit per nm 3 ) Electronic computer  1 Gbits per cm 2 Density of DNA computing

24. DNA computer  10 19 operations per Joule Electronic computer  10 9 operations per Joule Efficiency of DNA computing

25. DNA as Computational Tool

26. DNA as computing tool

27. Nucleotide:  purine or pyrimidine base  deoxyribose sugar  phosphate group Purine bases  A(denine), G(uanine) DNA sequences consist of  A, C, G, T Pyrimidine bases  C(ytosine), T(hymine) DNA as computing tool

31. {000} {001} {010} {011} {100} {101} {110} {111} All possible solutions

32. Negative selection

33. Selection principle

34. V0-1: 5'-AACCACCAACCAAACC V0-0: 5'-AAAACGCGGCAACAAG V1-1: 5'-TCAGTCAGGAGAAGTC V1-0: 5'-TCTTGGGTTTCCTGCA V2-1: 5'-TTTTCCCCCACACACA V2-0: 5'-TTGGACCATACGAGGA V3-1: 5'-CGTTCATCTCGATAGC V3-0: 5'-AGAGTCTCACACGACA V4-1: 5'-AAGGACGTACCATTGG V4-0: 5'-CTCTAGTCCCATCTAC V5-1: 5'-CAACGGTTTTATGGCG V5-0: 5'-GCGCAATTTGGTAACC V6-1: 5'-TAGCAGCTTCCTTACG V6-0: 5'-ACACTGTGCTGATCTC V7-1: 5'-CACATGTGTCAGCACT V7-0: 5'-TGTGTGTGCCTACTTG V8-1: 5'-GATGGGATAGAGAGAG V8-0: 5'-AATCCCACCAGTTGAC V9-1: 5'-ATGCAGGAGCGAATCA V9-0: 5'-GCTTGTTCAACCTGGT V10-1: 5'-CCCAGTATGAGATCAGV10-0: 5'-CTGTCCAAGTACGCTA V11-1: 5'-ATCGAGCTTCTCAGAGV11-0: 5'-TGTAGAGGCTAGCGAT Word design with 16 bases

35. Logic operations

37. Logic NOT operations

38. a  b Logic AND operations

39. a  ba  b Logic OR operations

40.  ((  h   f)   a)   ((  g   i)   b)   ((  d   h)   c)   ((  c   i)   d)   ((  a   g)   f) 3x3 knight problem

42. Selection module

43. magnet Positive selection module

44. magnet Positive selection module

45. Some pictures

46. 3.5mm