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Who am I?

Delve into the field of DNA computing, its molecular electronics, evolutionary biology applications, and theoretical implications. This comprehensive guide covers its history, potential, and comparison with traditional computing.

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Who am I?

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  1. Who am I?

  2. Who am I?

  3. Where to find me

  4. Where to find me

  5. Where to find me

  6. Course outline

  7. Course outline

  8. Course outline • Presentation • Essay on new molecular computing idea • and/or setting up a detailed webpage

  9. What is DNA computing?

  10. The field of DNA computing is concerned with the possibility of performing computations using biological molecules. What is DNA Computing? • 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.

  11. What is DNA Computing? 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 ...

  12. What is DNA Computing? 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 ...

  13. What is DNA Computing? 011001101010001 ATGCTCGAAGCT

  14. What is DNA Computing? • 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

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

  16. Biocomputing vs. Bioinformatics Biomolecular computing DNA computing

  17. Known CMOS limitations Gate length Relative Fab Cost 140 nm 16 80 nm parameters approach molecule size 4 4.0 60 nm 2.7 45 nm Inter-metal Dielectric K 1.6-2.2 1 1.6-2.2 <1.5 0.25 2011 2002 2005 2008 1999 Source: Texas Instruments and ITRS IC Design Technology Working Group

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

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

  20. DNA computers vs. conventional computers

  21. Speed of DNA computing Computer speed • number of parallel processors • number of steps each processor can perform per unit of time DNA computer • 3 grams of water contains 1022 molecules • massively parallel Electronic computer • advantage in number of steps performed per unit of time

  22. Density of DNA computing information per space unit perform per unit of time DNA computer • 106 Gbits per cm2 (1 bit per nm3) Electronic computer • 1 Gbits per cm2

  23. Efficiency of DNA computing DNA computer • 1019 operations per Joule Electronic computer • 109 operations per Joule

  24. DNA as Computational Tool

  25. DNA as computing tool

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

  27. DNA as computing tool

  28. DNA as computing tool

  29. DNA as computing tool

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

  31. Negative selection

  32. Selection principle

  33. Word design with 16 bases V0-1:5'-AACCACCAACCAAACCV0-0:5'-AAAACGCGGCAACAAG V1-1:5'-TCAGTCAGGAGAAGTCV1-0:5'-TCTTGGGTTTCCTGCA V2-1:5'-TTTTCCCCCACACACAV2-0:5'-TTGGACCATACGAGGA V3-1:5'-CGTTCATCTCGATAGCV3-0:5'-AGAGTCTCACACGACA V4-1:5'-AAGGACGTACCATTGGV4-0:5'-CTCTAGTCCCATCTAC V5-1:5'-CAACGGTTTTATGGCGV5-0:5'-GCGCAATTTGGTAACC V6-1:5'-TAGCAGCTTCCTTACGV6-0:5'-ACACTGTGCTGATCTC V7-1: 5'-CACATGTGTCAGCACTV7-0:5'-TGTGTGTGCCTACTTG V8-1: 5'-GATGGGATAGAGAGAGV8-0:5'-AATCCCACCAGTTGAC V9-1:5'-ATGCAGGAGCGAATCAV9-0:5'-GCTTGTTCAACCTGGT V10-1:5'-CCCAGTATGAGATCAGV10-0:5'-CTGTCCAAGTACGCTA V11-1:5'-ATCGAGCTTCTCAGAGV11-0:5'-TGTAGAGGCTAGCGAT

  34. Logic operations

  35. Logic operations

  36. Logic NOT operations

  37. Logic AND operations a b

  38. Logic OR operations ab

  39. 3x3 knight problem • ((h  f)a) • ((gi)b) • ((dh)c) • ((ci)d) • ((ag)f)

  40. 3x3 knight problem

  41. Selection module

  42. Positive selection module magnet

  43. Positive selection module magnet

  44. Some pictures

  45. 3.5mm

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