CS85, Prof. Neal Young
Spring '96, Dartmouth College
My initial project proposal was to find information pertaining more to
the biology side of DNA Computing. In my search to do this I found
that the web was scattered with pages about DNA Computing and there
was no real central place to search for it. Also, I spoke with
Biology Professor Bob Gross (Dartmouth College) about the problems
that could go wrong with some of the procedures used in some papers
(such as Merge, Separate, Copy, Detect, Amplify, and Extract), and he
seemed to think that any procedure done on DNA was not perfect. You
have to depend on the probability that it is correct when using the
precedures. So, in light of these two things, I decided to put
together a web page that included many links to papers and other ideas
on DNA Computing and Molecular Biology. Although it does not include
everyone or everything having to do with DNA Computing, it is an
excellent compilation of sources.
This page is designed to organize the topics related to DNA Computing
into one page, and bring in some aspects of Molecular Biology. It
includes links to papers, jump stations, home pages, articles, and
more for the layperson and researcher alike.
Constructing a Molecular Computer Len Adelman (20 pages).
- Len Adelman
Abstract. It has recently been suggested that under some
circumstances computers based on molecular interactions may be a
viable alternative to computers based on electronics. Here, some
practical aspects of constructing a molecular computer are considered.
Architecture, Engineering and Technology John Amenyo.
Introduction. In what manner can computers built using
nucleotide-based biomolecules, in the style of L. Adleman  be
compared to extant electronic mainframes, microcomputers and other digital information processing systems ?
In this note, I would like to revisit this question and give a
more "engineering-oriented" answer. Namely, I try to envision what the
"hardware" of a bio-computer (Adleman-style) would look like when it
becomes available. Of course, there are related questions such as
DNA-based Computers Workshop John Amenyo.
What is a
computer? John Amenyo.
Martyn Amos (home page)
Implementation of DNA Computations Martyn Amos, Alan Gibbons and
David Hodgson (10 pages).
This paper introduces a new model of computation that employs the
tools of molecular biology whose implementation is far more
error-resistant than extant proposals. We describe an abstraction of
the model which lends itself to natural algorithmic description,
particularly for problems in the complexity class NP. In addition we
describe a number of linear-time algorithms within our model,
particularly for NP-complete problems. We describe an in vitro
realisation of the model and conclude with a discussion of future
Eric Baum (home page)
Sequences Useful for Computation Eric Baum (6 pages).
Recent proposals for DNA based computing encode Boolean vector component values
with sequences of DNA. It has previously been assumed that sufficient length random subsequences could be used to encode
component values. However use of such subsequences will inadvertently result in
long complementary subsequences. Complementary subsequences of
sufficient length would stick to each other and cause mistakes or
delays in computation. We suggest some constraints on DNA subsequences
to be used in encodings, and describe maximal sets of subsequences
satisfying these constraints.
Running dynamic programming algorithms on a DNA computer
Eric B. Baum and Dan Boneh (7 pages).
We show that DNA computers are useful for running algorithms based on
dynamic programming. This class of algorithm takes advantage of the
large memory capacity of a DNA computer. We present algorithms for solving
certain instances of the knapsack problem, using a dynamic programming
approach. Unlike other algorithms for DNA computers, which are brute
force, dybamic programming is the same algorithm one would use to solve
(smaller) problems on a conventional computer.
with DNA Eric Baum (24 pages).
"These are transparencies from a talk given at the Organo
Electronic Materials Conference. Unfortunately, the drawings are not
Don Beaver (home
Computing Don Beaver (13 pages).
We design a molecular Turig Machine and determine the complexity
of the problems solvable by molecular computers. In [A94], a
combinatorial molecular experiment to solve the NP-complete problem of
Hamiltonian Path was proposed and implemented. Using our design, we
show that such molecular computers can in fact compute PSPACE, under
the generous assumptions implicit in [A94] fails to satisfy, we show
that molecular computers are limited to solving problems in P.
With DNA Don Beaver (10 pages).
We consider molecular models for computing and derive a DNA-based
mechanism for solving intractable problems through massive
parallelism. In principle, such methods might reduce the effect
needed to solve otherwise difficult tasks, such as factoring large
numbers, a computationally-intensive task whose intractability forms
the basis for much of modern cryptography.
Dan Boneh (home
Using a Molecular Computer Dan Boneh, Richard Lipton, and Chris
Dunworth (20 pages).
Recently Adleman has shown that a small traveling salesman problem
can be solved by molecular operations. In this paper we show how the
same principles can be applied to breaking the Data Encryption
Standard (DES). Our method is based on an encoding technique presented
by Lipton. We describe in detail a library of operations which are
useful when working with a molecular computer. We estimate that given
one arbitrary (plain-text, cipher-text) pair, one can recover the DES
key in about 4 months of work. Furthermore, if one is given
cipher-text, but the plain text is only known to be one of several
candidates then it is still possible to recover the key in about 4
months of work. Finally, under chosen cipher-text attack it is
possible to recover the DES key in one day using some preprocessing.
Computational Power of DNA Dan Boneh, Richard Lipton, Chris
Dunworth, and Jiri Sgall (15 pages).
We extend the results of Lipton to show how DNA based computers
can be used to solve the satisfiability problem for circuits. We show
that our methods enable random sampling of satisfying
assignemnts. Furthermore, we show how one can solve optimization
problems directly without first solving several decision
problems. Finally we suggest a procedure for evaluating functions in
the polynomial hierarchy.
Computers Error Resistant Dan Boneh and Richard Lipton (9 pages).
Recently Lipton showed that the formula satisfaction problem can
be solved using a DNA based computer. The algorithm ignored the
effects of errors that occur during biological experiments. In this
paper we show that Lipton's algorithm can be made resistant to
errors. In addition, we present a new circuit satisfaction algorithm
which can be made error resistant using the same techniques.
A Divide and
Conquer Approach to Sequencing Dan Boneh and Richard Lipton (6 pages).
We suggest an approach to sequencing based on a "divide and
conquer method Thisapproach eliminates the need for solving a hard
NP-complete problem which arises when using traditional sequencing
techniques. At the present time this algorithm has not been tried out
in the lab. However, computer simulations using parts of the human
genome provide some encouraging data.
DNA Computations Dan
Boneh and Richard Lipton (2 pages).
In this short note we point out that in some cases batching
computations on a molecular computer is very cheap. This is especially
useful for breaking cryptosystems and can be useful for other
applications as well.
Elton Glaser (home page)
DNA Models and
Algorithms for NP-complete Problems Eric Bach, Anne Condon, Elton
Glaser, and Celena Tanguay (22 pages).
Peter Kaplan (home page)
in Biomolecular Computation
Note: This page is still under
construction but when it is finished I think it will be worthwhile to
Lila Kari (home page)
the Arrival of Biological Mathematics Lila Kari (18 pages).
DNA Computing Based
on Splicing: The Existence of Universal Computers Lila Kari, Rudolf Freund
and Ghcorghc Paun (31 pages).
Splicing systems are generative mechanisms based on the splicing
operation introduced by Tom Head as a model of DNA recombination. We
prove that the generative power of finite extended splicing systems
equals that of Turing machines, provided we consider multisets or
provided a control mechanism is added. We also show that there exist
universal splicing systems with the properties above, i.e. there
exists a universal splicing system with fixed components which can
simulate the behaviour of any given splicing system, when an encoding
of the particular splicing system is added to its set of axioms. In
this way the possibility of designing programmable DNA computers based
on the splicing operation is proven.
DNA Computing Based
on Splicing: Universality Results Lila Kari, Rudolf Freund,
Ghcorghc Paun, and Erzsebet Csuhaj-Varju.
The paper extends some of the most recently obtained results on
the computational universality of extended H systems (with regular
sets of rules respectively with finite sets of rules used with simple
additional mechanisms) and shows the possibility to obtain universal
systems based on these extended H systems, i.e. the theoretical
possibility to design programmable universal DNA computers based on
the splicing operation. The additional mechanisms considered here
are: multisets (counting the numbers of copies of each available
string), checking the presence/absence of certain symbols in the
spliced strings, and organizing the work of the system in a
distributed way (like in a parallel communicating grammar system). In
the case of multisets we also consider the way of simulating a Turing
machine (computing a partial recursive function) by an equivalent H
system (computing the same function), in the other cases we consider
the interpretation of algorithms as language generating devices, hence
the aim is to reach the power of Chomsky type-0 grammars, the standard
model for representing algorithms being equivalent with Turing
machines taken as language generators.
Distributed Systems Based on Splicing Lila Kari, Ghcorghc Paun,
and Erzsebet Csuhaj-Varju (21 pages).
We define a symbol processing mechanism with the components (test
tubes) working as splicing schemes in the sense of T. Head and
communicating by redistributing the contents of tubes (in a similar
way to the separate operation of Lipton-Adelman). (These systems are
similar to the distributed generative mechanisms called Parallel
Communicating Grammar Systems.) Systems with finite initial contents
of tubes and finite sets of splicing rules associated to each
component are computationally complete, they characterize the family
of recursively enumberable languages. The existence of universal test
tube distributed systems is obtained on this basis, hence the
theoretical proof of the possibility to design universal programmable
computers with the structure of such a system.
Richard Lipton (home page)
Using DNA to
Solve SAT Richard Lipton (8 pages).
We show how to use DNA experiments to solve the famous "SAT" problem
of Computer Science. This is a special case of a more general method
of  to solve NP-complete problems. The advantage of these results
is the huge parallelism inherent in DNA based computing. It has the
potential to yield vast speedups over conventional electronic based
computers for such search problems.
John Reif (home page)
Molecular Computation: Models and Simulations
John Reif (35 pages).
This paper describes techniques for massively parallel computation at
the molecular scale, which we refer to as molecular parallelism.
While this may at first appear to be purely science fiction, already
Adelman [A 94] has employed molecular parallelism in the solution of
the Hamiltonian path problem of n nodes using O(n^2) lab steps on
recombinant DNA of length O(n log n) base pairs. He successfully tested
his techniques in a small lab experiment on DNA for a 7 node
Hamiltonian path problem. Lipton [L 94] showed that finding the
satisfying inputs to a Boolean formula of size n can be done in O(n)
lab steps using DNA of length O(n log n) base pairs. This recent work
by Adleman and Lipton in molecular parallelism considered only the
solutionof NP search problems, and provided no way of quickly
executing lengthy computations by purely molecular means, the number
of lab steps depended linearly on the size of the simulated formula.
This paper describes techniques for quickly executing lengthy
computations by the use of molecular parallelism. We demonstrate that
molecular computations can be done using short DNA strands by more or
less conventional biotechnology engineering techniques within a small
number of lab steps.
Diana Rooß (home
the Power of DNA-Computers Diana Rooß and Klaus Wagner (20
In [Adl94] Adleman used biological manipulations with DNA strings
to solve some instances of the Directed Hamiltonian Path Problem.
Lipton [Lip94] showed how to extend this idea to solve any NP
problem. We prove that exactly the problems in P^NP = delta(sub 2,
super P) can be solved in polynomial time using Lipton's model.
Various modifications of Lipton's model are investigated, and it is
proved that their computational power in polynomial time can be
characterized by one of the complexity classes P, delta(sub 2, super
P), delts(sub 3, super P) or even PSPACE. Restricting Lipton's model
to DNA strings of logarithmic length one can compute exactly the
problems in L.
Paul Rothemung (home page)
and Restriction Enzyme Implementation of Turing Machines Paul Wilhelm Karl
Bacteria employ restriction enzymes to cut or restrict DNA at or
near specific words in a unique way. Many restriction enzymes cut the
two strands of double-stranded DNA at different positions leaving
overhangs of single-stranded DNA. Two pieces of DNA may be rejoined or
ligated if their terminal overhangs are complementary. Using these
operations fragments of DNA, or oligonucleotides, may be inserted and
deleted from a circular piece of plasmid DNA. We propose an encoding
for the transition table of a Turing machine in DNA oligonucleotides
and a corresponding series of restrictions and ligations of those
oligonucleotides that, when performed on circular DNA encoding an
instantaneous description of a Turing machine, simulate the operation
of the Turing machine encoded in those oligonucleotides. DNA based
Turing machines have been proposed by Charles Bennett but they invoke
imaginary enzymes to perform the state-symbol transitions. Our
approach differs in that every operation can be performed using
commercially available restriction enzymes and ligases.
Nadrian Seeman (home page)
Ned Seeman's Laboratory
"Our laboratory is investigating unusual DNA molecules in model
systems that use synthetic molecules. Our interest in these molecules
was originally stimulated by a desire to characterize Holliday
junctions. These are four-arm branched DNA molecules that are found to
be structural intermediates in genetic recombination. The focus of the
work on these unusual molecules is to characterize their structure,
dynamics and thermodynamics, and to establish the relationship between
these properties and their biological function. In the last few years,
the symmetry and crossover topology of the 4-arm junction has been
characterized and analyzed. The study of recombination intermediates
has been extended by constructing and analyzing molecules with double
crossovers, and by exploring broader classes of multi-stranded
molecules, called antijunctions and mesojunctions."
Warren Smith (home page)
List of publications
by Smith, including some (non-hyperlinked) DNA papers.
An opinionated, but reasonably short, summary
of the Mini DIMACS Workshop on DNA based computers, held at Princeton
University on April 4 1995. Warren Smith (4 pages).
Erik Winfree (home page)
Restricted and Unrestricted Models of Molecular Computation Erik
Winfree (8 pages).
In [Li1] and [Ad2] a formal model for molecular computing was
proposed, which makes focused use of affinity purification. The use
of PCR was suggested to expand the range of feasible computations,
resulting in a second model. In this note, we give a precise
characterization of these two models in terms of recognized
computational complexity classes, namely branching programs (BP) and
nondeterministic branching programs (NBP) respectively. This allows
us to give upper and lower bounds on the complexity of desired
computations. Examples are given of computable and uncomputable
problems, given limited time.
the Computational Power of DNA Annealing and Ligation Erik Winfree
In [Winfree] it was shown that the DNA primitives of Separate,
Merge, and Amplify were not sufficiently powerful to invert functions
defined by circuits in linear time. Dan Boneh et al [Boneh] show that
the addition of a ligation primitive, Append, provides the missing
power. The question becomes, "How powerful is ligation? Are Separate,
Merge, and Amplify necessary at all?" This paper proposes to
informally explore the power of annealing and ligation for DNA
computation. We conclude, in fact, that annealing and ligation alone
are theoretically capable of universal computation.
Creation: The Coming Era of Nanotechnology by
K. Eric Drexler.
Molecular engineering: An
approach to the development of general capabilities for molecular
manipulation K. Eric Drexler.
Development of the ability to design protein molecules will open a
path to the fabrication of devices to complex atomic specifications, thus
sidestepping obstacles facing conventional microtechnology . This path will
involve construction of molecular machinery able to position reactive groups to
atomic precision. It could lead to great advances in computational
devices and in the ability to manipulate biological materials. The
existence of this path has implications for the present.
is Beautiful: a collection of nanotechnology links
Imagine a technology so powerful that it will allow such feats as
desktop manufacturing, cellular repair, artificial intelligence,
inexpensive space travel, clean and abundant energy, and environmental
restoration; a technology so portable that everyone can reap its
benefits; a technology so fundamental that it will radically change
our economic and political systems; a technology so imminent that most
of us will see its impact within our lifetimes. Such is the promise
Paul Hengren (home page)
Lots of biology info and jump points.
Reference Information What it is, what it's not.
BioGuide - PCR
2-D Gel Electrophoresis
And The Quantitation Of Gene Expression
Two-dimensional gel electrophoresis
Biology - Miscellaneous
Biology, Biochemistry Databases
Theory and the Theory of Molecular Machines
Toward Molecular Manufacturing
Enzymes - Background Paper
Watson and Crick's description, in 1953, of the double helical
structure of theDNA molecule (See Classic Collection- The Structure of
DNA) opened the door to a new era in biological understanding and
research. Scientists, now knowing the molecular structure of the
hereditary molecule, could begin both to elucidate and to manipulate
its function. These new studies were, however, dependent on the
discovery and use of the many enzymes that are able to modify or join
existing DNA molecules, or to aid in the synthesis of new DNA
REBASE Home Page
Dr. Richard J. Roberts' Restriction Enzyme Database
(Electronics and Biotechnolgy Advanced) Project: Towards
Biocomputation from the Commission of the European Community
Center for Discrete
Mathematics and Theoretical Computer Science
Sequence Classification Using Compression-Based Induction David
Loewenstern, Haym Hirsh, Peter Yianilos, and Michiel Noordewier (14
Inductive learning methods, such as neural networks and decision
trees, have become a popular approach to developing DNA sequence
identification tools. Such methods attempt to form models of a
collection of training data that can be used to predict future data
accurately. The common approach to using such methods on DNA sequence
identification problems forms models that depend on the absolute
locations of nucleotides and assume independence of consecutive
nucleotide locations. This paper describes a new class of learning
methods, called compression-based induction (CBI), that is geared
towards sequence learning problems such as those that arise when
learning DNA sequences. The central idea is to use text compression
techniques on DNA sequences as the means for generalizing from sample
sequences. The resulting methods form models that are based on the
more important relative locations of nucleotides and on the dependence
of consecutive locations. They also provide a suitable framework into
which biological domain knowledge can be injected into the learning
process. We present initial explorations of a range of CBI methods
that demonstrate the potential of our methods for DNA sequence
The Journal of
The National Center for
Diabetes Center DNA Core Facility
NEC Research Institute Home
Computers: A Mini DIMACS Workshop
DIMACS Workshop on DNA Based Computers
THE HISTORY OF
On November 11 1994, Leonard Adleman published a paper in
Science describing the "Molecular Computation of Solutions of
Combinatorial Problems". This was the first ever implementation of a
DNA-based computer. Since then, many advancements have been proposed
to refine the protocol for programming a DNA computer to reduce the
complexity of the operations and eliminate errors. [2,3] Despite their
respective complexities, biological and mathematical operations have
some similarities: The very complex structure of a living being is the result of applying
simple operations to initial information encoded in a DNA sequence.
The result f(w) of applying a computable function to an argument w can
be obtained by applying a combination of basic simple functions to w.
For the same reasons that DNA was presumably selected for living
organisms as a genetic material, its stability and predictability in
reactions, DNA strings can also be used to encode information for
Explanations of some NP-complete problems.
Computation of Solutions to Combinatorial Problems from Science.
The tools of molecular biology were used to solve an instance of
the directed Hamiltonian path problem. A small graph was encoded in
molecules of DNA, and the "operations" of the computation were
performed with standard protocols and enzymes. This experiment
demonstrates the feasibility of carrying out computations at the
OF DNA MAY BECOME THE FAST COMPUTER OF THE FUTURE from NY Times.
DNA Computing from Science.
Computer In A Bottle: Your laptop may soon lose its cool hard
silicon chips, in exchange for DNA. The stuff of life itself.
Genie by Thomas A. Bass.
It's a hundred times faster than the best serial
supercomputer. It's a billion times more energy efficient. It's a
trillion times denser than the best storage media. It's a teaspoonful
of DNA that's a computer! And Leonard Adleman invented it.
Produced by Dax Burkhart '96, Dartmouth College,
for COSC 85/185: Novel
Frameworks in Theoretical Computer Science,
Professor Neal Young.
26 May 1996
This final project varies greatly from original project proposition
because after searching the web, I found that the links to DNA
Computing papers and pages were scattered throughout the web. So I
decided to bring them together. I admit that the above does not
contain ALL sources for DNA Computing, but it is an excellent start.