Lecture Notes: DNA Computing

Small DNA Computer Timeline

1994 – Leonard Adleman demonstrates proof-of-concept with first DNA Computer calculation of Traveling Salesman Problem. (His computation chugged along at 100 trillion floating point operations per second)

1997 – Researchers at the University of Rochester develop DNA Logic Gates.

DNA Logic Gates

2002 – Researchers at the Weizmann Institute of Science in Rehovot, Israel a programmable molecular computing machine composed of enzymes and DNA molecules.

DNA Computer runs 330 Trillion operations per second

2004 – Researchers at the Weizmann Institute unveil a DNA computer with an input and output module that could theoretically identify cancerous cells and release anti-cancer drugs to counter them.

2009 – Bio computing systems were combined with silicon based chips for the first time. An enzyme based OR / AND with resets logic system is accomplished with field-effect silicon chips.

2012 Harvard breaks previous record of DNA storage, crams 700 terabytes of data into a single gram.

http ://www .extremetech .com /extreme /134672-harvard -cracks -dna -storage -crams -700-terabytes -of -data -into -a -single -gram

DNA The silicon Replacement?

As it stands today we are converging on silicon's theoretical transistor limit of the 10 nm nanometer limit due to quantum tunneling.

If we can solve the quantum tunneling problem we could get to a transistor one molecule wide ie 1 nm but that still not much of an improvement of transistor density.

http ://computer .howstuffworks .com /small -cpu 2.htm

DNA still won't be replacing the every mans computer anytime soon even though they seem incredibly fast, and has great storage density (volumetric vs planar) because every new calculation needs a lot of help from us still.

Thus, while transistors in a silicon computer can be reused for multiple calculations, a DNA strand is only used once. Essentially, you have to make a new computer for every new calculation. On the upside, every multi-cellular organism on the planet contains DNA of varying combinations, so we aren’t likely to have a shortage anytime soon. http ://en .wikipedia .org /wiki /DNA _computing

DNA CALCULATIONS ONLY APPEAR FAST! I’ll say that again DNA CALCULATIONS ONLY APPEAR FAST! The individual calculations are actually quite slow but they appear fast because the calculations are massively parallel. Think of it as mix a bunch of DNA together with the right ingredients such as enzymes, and all strands interact with each other at the same time. Also the DNA answers to the calculations Don't make it easy to read off of the DNA molecules, a person still has to re-sequence after the DNA does its thing. This can take 24 hours, let alone read off the answer from the sequences.

http ://www .medicalnewstoday .com /articles /240145.php

Another thing to consider is that the DNA Interactions are not perfect. Between mismatched base pairs, and outside forces acting on the DNA from other molecules as such error propagates the larger the problem set is so the calculations have a smaller and smaller chance of getting the correct answer. Additionally is DNA molecules can dissociate in if left alone for long enough on their own.

Well with all those problems why would anyone in their right mind even consider using dna for computations.

1) So long as there are multi-cellular organisms, there will be DNA strands to use. Least of all synthesizing more in the lab.

2) DNA chips can be made cleanly, unlike most if not all silicon based computers.

3) DNA computers would be much smaller than modern computers, while holding vast amounts of data. The human genome has 3.17 billion pairs *2 bits per pair ~ 6.24 billion bits in 1 cell * 10 to 100 trillion cells ~ thats a mind staggering amount of bits of storage in a human~6.24*10^24

4) The ability for massive parallelism processing is very nice.

5) Low power usage. a human needs about 2000 Kcals a day ~ 97 watts

assume each cell (50 trillion) body does one calculation/sec + brain has neuron connects to 1000 other neurons- so every time a neuron fires, about 1000 other neurons get information about that firing. If we multiply all this out we get 100 billion neurons X 200 firings per second X 1000 connections per firing ~ 20 million billion calculations per second. 97 J/s /(2*10^17 calc/s)= 5*10^-16 J/calculation http ://www .ualberta .ca /~chrisw /howfast .html WOW!!!!!!

World's First DNA Computer

Adleman's first DNA computation solved a traveling salesman problem of seven cities. The method of doing so is simple. Each city is represented by a unique sequence of base pairs . Connections between two cities are created from a combination of the complement of the first half of one city, and the complement of the second half of the other city. In this way DNA representing the trip will be created with one strand representing a sequence of cities and the complementing strains representing a series of connections.

http ://ocw .mit .edu /courses /biology /7-349-biological -computing -at -the -crossroads -of -engineering -and -science -spring -2005/

Miami New York route encoding = route solution

CTACGG ATGCCG + GCTA C= CTACGGATGCCG

GCCTAC

http ://arstechnica .com /reviews /2 q 00/dna /dna -1.html. finding the solution involves sorting the DNA by length through a process known as electrophoresis.

While Adelman's techniques leave a lot to be compared to silicon chips and computers (remember Silicon Technology has had 50 or so years to develop) ie a new computation would involve creating a new experiment so a lot of current research is being done on creating logic gates with out of DNA and many have been found I'll just look at one example.

DNAzymes

Catalytic DNA (deoxyribozyme or DNAzyme) catalyze a reaction when interacting with the appropriate input, such as a matching oligonucleotide. These DNAzymes are used to build logic gates analogous to digital logic in silicon; however, DNAzymes are limited to 1-, 2-, and 3-input gates with no current implementation for evaluating statements in series.

NOT gate

Another type of molecular logic gate is the NOT gate. In this case, the catalytic core of the enzyme has been modified to include a stem-loop region that regulates enzyme activity. If the stem-loop is closed, the enzyme is active. However, when an input DNA is added, it hybridizes to the stem-loop region and alters the gate molecule's conformation. The conformational change causes the enzyme to become inactive, preventing cleavage of the substrate to produce output DNA. i.e a NOTz gate is active unless a single input iz is added, which inactivates the gate (see diagram below).

https://digamma .cs .unm .edu /wiki /bin /view /McogPublicWeb /MolecularLogicGates