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DNA Computing DCS 860A-2008 Team 3 December 20, 2008 Marco Hernandez, Jeff Hutchinson, Nelson Kondulah, Kevin Lohrasbi, Frank Tsen

DNA Computing

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DNA Computing. DCS 860A-2008 Team 3 December 20, 2008 Marco Hernandez, Jeff Hutchinson, Nelson Kondulah, Kevin Lohrasbi, Frank Tsen. What is a Computer?. Until the mid 20 th century the term referred to a person. Turing Machine (1936 – 37) - PowerPoint PPT Presentation

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Page 1: DNA Computing

DNA ComputingDCS 860A-2008 Team 3

December 20, 2008

Marco Hernandez, Jeff Hutchinson, Nelson Kondulah, Kevin Lohrasbi, Frank Tsen

Page 2: DNA Computing

What is a Computer?

• Until the mid 20th century the term referred to a person.

• Turing Machine (1936 – 37)– A ‘machine’, capable of maintaining state, which

operates on a ‘tape’ a series of rudimentary instructions

• Universal Turing Machine (1936 - 37)– All purpose machine that can run a sequence of

instructions of any arbitrary ‘Turing’ machine.

Page 3: DNA Computing

Computing Machines

Shapiro, E. and Y. Benenson, Computers To Life. Scientific American, 2006: p. 45-51.

Page 4: DNA Computing

DNA Computing

• In DNA computing, the scientist is taking advantage of the information content (the Watson-Crick pairing) of DNA’s component units. These are Nucleic Acids and they bind specifically as follows:– Adenosine Thymidine and;– Cystosine Guanidine.

• Is this a programming language?

Page 5: DNA Computing

Genetic Algorithms

• Genetic algorithms are highly parallel mathematical algorithms that transform populations of individual mathematical objects (typically fixed-length binary character strings) into new populations using operations patterned after – Natural genetic operations such as sexual

recombination (crossover) and – Fitness proportionate reproduction (Darwinian

survival of the fittest)

Koza, J.R. Genetically breeding populations of computer programs to solve problems in artificial intelligence. in Second International Conference on Tools for AI. 1990. Herndon, VA: IEEE Computer Society Press.

Page 6: DNA Computing

DNA Computing

• In 1994, Leonard Aldleman (Rivest, Shamir, Adleman) used DNA as a form of computer to solve a seven node graph problem.

• From this first use, people have seen its potential in exploring the intersection of biology, chemistry, medicine, mathematics and computer science.

• Research in DNA computing has primarily focused on solving mathematical problems and more recently on nanotechnology.

Page 7: DNA Computing

DNA Computing

• Paul W.K. Rothemund of the California Institute of Technology, is doing active research in the creation of nanoscale shapes.

Paul W.K. Rothemund Home Page. 2008 [cited 2008 December 6, 2008]; Paul W. K. Rothemund Research Page]. Available from: http://www.dna.caltech.edu/~pwkr/.

Page 8: DNA Computing

DNA Computing

• In 2005, researchers at the Seoul National University developed a Genetic Programming method that involved DNA in silico A decision tree implementation for the diagnosis of Acute Myelogenous and Acute Lymphoblastic leukemia (AML/ALL) was implemented in DNA.

• Given a sample of a patients DNA, its disease status is determined by matching it against the decision list in the population.

Page 9: DNA Computing

DNA Computing

• Researchers at the Seoul National University have developed a probalistic graphical model based on undirected graphs, called the hypernetwork model, and applied it to the medical diagnosis of disease.

• The authors used simulated DNA computing to create a predictive model for Cardiovascular (CV) disease.

Page 10: DNA Computing

DNA ComputingRuns DT SVM BN O-HN E-HN

1 93.860 93.86 92.110 83.478 98.261

2 95.614 98.246 98.246 86.957 93.043

3 93.86 96.491 93.860 88.696 95.652

4 89.474 90.351 91.228 83.478 94.783

5 93.860 93.86 92.983 84.378 93.913

6 85.965 89.474 87.719 84.378 96.522

7 92.105 93.86 92.983 81.739 97.391

8 92.983 97.368 95.614 83.478 96.522

9 94.737 96.491 95.614 83.478 97.391

Avg 92.495 94.445 93.373 84.451 95.942

p-value 0.005 0.111 0.023 0.000 -

The table above shows the models classification results as compared to other predictive tools: SVM (Support Vector Machine); Bayesian networks, Ordinary Hypernetwork, and Evolved Hypernetwork. Each model was run nine times with 20% of the original data in each run

Page 11: DNA Computing

DNA Computing• In recent years, Ehud Shapiro of the Weizmann

Institute has worked on developing a DNA-based computer. His research group produced one capable of diagnosing cancer in cells and releasing drug molecules in response

• In 2001, his team announced the creation of an autonomous DNA computer, i.e. once the input and ‘software’ molecules were placed in solution, computation commenced to completion with no human intervention, this managing to connect the DNA computer to its biochemical environment by sensing the state of its molecular output.

Page 12: DNA Computing

DNA Computing• In 2004, Researchers from the Weizmann Institute

developed autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression

• The research team designed a two state molecular automaton capable of detecting a genetic prostate cancer marker. The automaton is designed to release a biologically active molecule on positive diagnosis and its suppressor molecule on negative diagnosis.

• Is this a ‘nanobot’?

Page 13: DNA Computing

DNA Computing

• Questions ?