Introduction to Biocomputing:

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Introduction to Biocomputing Structure (DNA
RNA)
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• genome biological information in an organism
• DNA deoxyribonucleic acid, carries genome of
  cellular lifeforms
• RNA ribonucleic acid, carries genome of some
  viruses, carries messages within the cell
• bases the four bases found in DNA are
• adenine (A), cytosine (C), guanine (G),
• and Thymine (T) in a double helix of DNA,
• bonds are always A--T or C--G thus a single
• strand of DNA carries the information about
• the strand it would bond to
• So DNA can be thought of as a base 4 storage
  medium, a linear tape containing information in
  a 4-character alphabet

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DNAthe double helix
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DNAdirection
http//www.swbic.org/products/clipart/images/dna2.
jpg
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RNAThymine (T) replaced by Uracil (U) and
deoxyribose replaced by ribose
http//www.swbic.org/products/clipart/images/rna.j
pg
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comparison
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Translation DNA ? rRNA ? mRNA ? tRNA ? protein
http//www.swbic.org/products/clipart/images/dogma
g.jpg
http//www.swbic.org/products/clipart/images/trans
lation.jpg
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DNA provides the basic code.RNA copies this
code from the DNA and used this information to
form a string of amino acidsi.e., a
protein.Proteins are the machines that make
all living things function
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• Central Dogma

Before the discovery of retroviruses and prions,
this was believed to be the basic mechanism of
inheritance in all living things
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Relative sizes 10-18 electron 10-15 proton,
neutron 10-14 atomic nucleus 10-10 water
molecule (angstrom) 10-9 (nanometer, nm), one
DNA twist 10-8 wavelength of UV light 10-7
thickness of cell membrane 10-6 diameter of
typical bacterium (micron, mm) 10-5 diameter of
typical cell 10-4 width of human hair 10-3
diameter of sand grain (millimeter, mm) 10-2
diameter of nickel (centimeter, cm) 100 1 meter
nanotechnology molecules, atoms
0.18 or 0.13 mm, Pentium 4 wire width
2-10 mm, typical MEMS feature size
35 mm--one side of Pentium 4 chip

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• Why is biomolecular computing attractive?
• Size
• --typical bacterium has diameter on ht order of
  10-6 m. (1
• micron)
• --one twist of DNA double helix is on the order
  of 10-9 m.
• (nanometer scale)
• Power requirements should be low
• Massive parallel computation is theoretically
  possible
• I/O can be two-dimensional
• Instabilities of quantum systems are much less of
  a problem here

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• What are the disadvantages?
• Speed--typical reaction can take hours or days
• Error rates--may be unacceptably high may be
  introduced by mechanical steps in proocessing
  data
• I/O--we do not yet have efficient mechanisms for
  doing input/output with these systems
• Herd property--we can affect a mixture of data
  items we cannot in general pick out one specific
  item biomolecular computing is inherently
  parallel
• Exponential growth in size of computation--it may
  be that the speed barrier in traditional
  computing is replaced by a size barrier in
  biomolecular computing--we may need too much
  biological material to solve a reasonable sized
  problem for the computation to be feasible

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What interesting projects can build on our
knowledge of traditional computer engineering?

• structural designsDNA computing
• chemical designsusing proteins as signals

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• Computing using DNA structures
• polynucleotide a single DNA strand
• oligonucleotide short, single-stranded DNA
  molecule, usually less than 50 nucleotides in
  length
• In DNA computing, specific oligonucleotides are
  constructed to represent data items.
• nucleotide phosphate group sugar one of the
  4 bases (A,C,G,T) the phosphate end is labeled
  5, the base end, 3
• Example in Adelmans seminal 1994 paper,
  oligonucleotides of length 20 were built to
  represent vertices and edges in a given graph

Vertex V1
Vertex V2
Edge V1-V2
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DNA computing (structural, digital)

• Possible operations on DNA
• building up custom oligonucleotide sequences to
  represent parts of your data
• splitting--can be done by heating, e.g.
• recombining--can be done by cooling
• cutting strand at a particular site
• sticking two fragments together (at their ends)
• sorting by some string property (including
  length)

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• So-----DNA computing
• uses structure of the DNA
• relies on mechanical operations
• answers self-assemble
• basic steps
• encode the problem
• make a solution of problem fragments
• cool the solution so fragments will form longer
  strands
• filter out the answers you want

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Example solving graph problems

• Encode vertices and edgesuse DNA properties to
  encode graph structure
• Mix up a solution of your fragments
• Cool down, get resulting paths, spanning
  trees, etc.

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Standard cell architectures, FPGAsThe BioBrick
Project

• Basic idea (after Prof. Tom Knght, MIT)
• gates are functional units
• Ends of gates are standard join DNA
  sequencesreserved for this purpose
• So we can build computational chains easily
• Web page http//parts.mit.edu/registry/index.php/
  Main_Page

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• Other applications of DNA computing
• general computing using sticker language
• study of relationship between traditional
  architectures and DNA configurations
• ---FSMs-linear DNA
• ---stack machines--branching DNA
• ---Turing machines (general purpose
  computers)--
• sheet DNA

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• Other applications of DNA computing (continued)
• 3-D self-assembled structures
• walking and rolling DNA
• structures for nanotube assembly (recently
  reported in Science)