DNA Computing

BY

DIVYA TADESERA

Contents

Introduction

History and its origin

Relevancy of DNA computing in

1. Hamilton path problem(NP problem)

2. Cryptography

3. Steganography

Advantages

Introduction

DNA(Deoxyribonucleic acid) is the genetic blueprint of any organism.

Strands of DNA are long polymers of millions of linked nucleotides.

The nucleotides that make up these polymers are named after the nitrogen base that it consists of; Adenine (A), Cytosine (C), Guanine (G) and Thymine (T).

These nucleotides will only combine in such a way that C always pairs with G and T always pairs with A.

Therefore it is also known as Molecular computing.

Cont’d..

DNA computing or molecular computing are terms used to describe utilizing the inherent combinational properties of DNA for massively parallel computation.

enough DNA, one can potentially solve huge mathematical problems by parallel search.

This tells us that a man can compute more faster than a conventional computer which uses more hardware for massive parallelism

History and its origin

In early 1994, Adleman put his theory of DNA computing to test on a problem called the Hamiltonian Path problem also known as Traveling Salesman Problem.

Adleman’s DNA computing test is first done on a NP problem since it is a type of problem that is difficult for conventional computers to solve.

Hamilton path problem

Hamilton path problem is a non-deterministic polynomial time problem (NP).

As we need to check all possible solutions in order to get the correct answer the problem is termed to be non deterministic.

Any algorithm that runs on a non-deterministic machine in polynomial time is called a nondeterministic polynomial time problem

Hamilton path problem

‘Traveling Salesman’ Problem representing the 7 cities and one way streets between them

Rules: 1. The path must start at city A and end at city G.

2. Of those paths, the correct paths must pass through all 7 cities at least once.

3. The final path(s) must contain each city in turn.

Cont’d..

The ‘correct’ answer was determined by filtering the strands of DNA according to their end-bases to determine which strands begin from city A and end in city G and discarding those that did not.

The remaining strands were then measured through electrophoretic techniques to determine if the path they represent has passed through all 7 cities.

Cont’d..

Finally the resulting sets of strands were examined individually to determine if they contained each city in turn. That strand or strands that remained was then determined to be the answer or equivalent answers

These resulting individual strands are then combined in opposite directions to form DNA that is able to handle massive parallelism

Cryptography

Cryptography is a kind of secret writing(hiding the messages which we wish to).

It scrambles plaintext (ordinary text) into ciphertext (encrypted text)known as encryption and then back again from encrypted to plain text known as decryption.

Public Key Encryption

DNA is also termed as information carrier.

DNA computing may not be fast but it is massively parallel. With the right kind of setup, it has the potential to solve huge mathematical problems.

 DNA computing represents a serious threat to various powerful encryption schemes such as the Data Encryption Standard (DES).

Cont’d..

As we know that DNA can be used to break codes then it is clear that it can encrypt data.

Various groups have suggested using the sequence of nucleotides in DNA (A for 00, C for 01, G for 10, T for 11) for just this purpose.

One idea is to not even bother encrypting the information but simply burying it in the DNA so it is well hidden, a technique called DNA steganography.

Steganography

cryptography is the practice of protecting the contents of a message alone.

steganography is concerned with concealing the fact that a secret message is being sent, as well as concealing the contents of the message.

In order to synthesize a secret-message DNA containing an encoded message 69 nucleotides long flanked by forward and reverse PCR primers, each 20 nucleotides long

Cont’d..

We prepare a concealing DNA that is physically similar to the secret-message DNA by adding with a 56 bit key.

Doing this way, secures unique DNA configuration that is able to perform massive parallelism.

Although this problem has already been solved using conventional techniques in a much shorter time than proposed by the DNA methods, the DNA models are much more flexible, potent, and sender of cost effective.

Advantages

Speed – Conventional computers can perform approximately 100 MIPS (millions of instruction per second). On the other hand DNA computers(humans) can perform 100 times faster than the fastest computer.

Minimal Storage Requirements – DNA stores memory at a density of about 1 bit per cubic nanometer where conventional storage media requires 12-10 cubic nanometers to store 1 bit.

Minimal Power Requirements – As DNA doesn’t require any power source there is no comparison with the conventional computers that use.

Limitations

 It requires an exponential resource in terms of memory. Although DNA can store a trillion times more information than current storage media, the way in which the information is processed necessitates a massive amount of DNA if larger-scale problems are to be solved. 

 DNA strand synthesis is liable to errors, such as mismatching pairs, and is highly dependent on the accuracy of the enzymes involved.

Conclusion

Conventional computers and their software updates in future , results in building up cholesterol levels in persons arteries.

It is obvious that DNA computers are more flexible.

References

http://www.giac.org/paper/gsec/1617/dna-dna-computing-security-practices-future-genes/102969

http://www.technologyreview.com/view/412610/the-emerging-science-of-dna-cryptography/

http://www.polestarltd.com/ttg/isspeeches/051403/index.html

THANK YOU