DNA as a solution of computational problems Radosław Łazarz

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Presentation transcript:

DNA as a solution of computational problems Radosław Łazarz An introductrion to DNA-based computing Examples of succesful implementations: Hamiltonian path problem Turing-like finite automaton Tic-Tac-Toe Predictions about the future

Why DNA? ~750 mB large number od parallel processes extraordinary energy efficiency survived around 3 billion years of demanding tests as a data carrier multiple similarities with Turing machine

Hamiltonian Path Problem Leonard M. Adelman (1994) Tools: Watson-Crick pairing Polymerases Ligases Nucleases Agarose gel electrophoresis DNA synthesis Bruteforce algorithm 7 days in laboratory…

Finite automaton 2 states 4 transition rules Fok I and ligase no additional energy source close to Turing completeness

DNA Doctor? in vitro vs. in vivo input: mRNA as disease indicators output: antisense DNA molecule

Molecular Array of YES and ANDANDNOT gates (MAYA) allosterically regulated deoxyribozymes input: oligonucleotides output: fluorescencent molecules 15 minutes per move MAYA II

What next? Other successful applications: Important problems: self assembly of ‘Wang’ tiles boolean satisfiability problem (SAT) designing materials by specifying a series of DNA orders Important problems: designing enzymes stochastic nature of biological processes monitoring results „But biology and computer science - life and computation - are related. I am confident that at their interface great discoveries await those who seek them.”

If you want to learn more: “Computing with DNA” - Leonard M. Adleman; Scientific American, August 1998 “Molecular Computation of Solutions to Combinatorial Problems.” - Leonard M. Adleman; Science, November 1994. “DNA Solution of Hard Computational Problems.” - Richard J.Lipton; Science, April 1995. “Bringing DNA Computers to Life.” - Ehud Shapiro, Yaakov Benenson; Scientific American, May 2006 “A Deoxyribozyme-Based Molecu­lar Automaton.” - Milan N. Stojanovic and Darko Stefanovic; Nature Bio­technology, September 2003 “DNA Computers for Work and Play” - Joanne Macdonald, Darko Stefanovic and Milan N. Stojanovic; Scientific American, November 2008 https://digamma.cs.unm.edu/wiki/bin/view/McogPublicWeb/MolecularAutomataMAYAII “Logical Computation Using Algorithmic Self-Assembly of DNA Triple Crossover Molecules.” - Chengde Mao, Thomas H. LaBean, John H. Reif, Nadrian C. Seeman; Nature, September 2000 “Nanotechnology and the Double Helix” - Nadrian C. Seeman; Scientific American, June 2004 http://student.agh.edu.pl/~lazarz/MOwNiT

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