Surveyon Killer Applications, Recent Advancements and Basic Arithmetic Operations in DNA Computing Paradigm.

Date of Submission

December 2001

Date of Award

Winter 12-12-2002

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science

Department

Theoretical Statistics and Mathematics Unit (TSMU-Bangalore)

Supervisor

Barua, Rana (TSMU-Kolkata; ISI)

Abstract (Summary of the Work)

After a long journey of more than half a century of semiconductor technology based electronic computing devices it seems that limiting saturation point is not far away when electronic computing era may start touching its natural physical limits due the difficulties in fabrication technology like lithography bandwidth. Still hard problems possibly will remain insurmountable even then. A new ray of hope has come from the experimental demonstration by Leonard Adleman [Adle94] by solving an NP complete problem, namely the Hamiltonian Path Problem (HPP), using none other but the DNA (deoxirebonuclic acid) strands, the nature's choice as carrier's of the definition of life.In fact even before anyone could think of performing actual experiment demon- strating direct application of DNA like large organic compounds as computing tools R.P. Feynman in his visionary lecture (Feynman61] envisioned molecular level com- puting. But the road was not easy, since to perform computing in a controlled fashion, structures (tools) must be stable and suitable to encode information, and DNA nano-technology achieved successes in this type of controls only later. With the help of these DNA nano-technology tools in 1994 for the first time Adleman car- ried out an biological experiment for encoding and solving HPP using DNA strands and standard DNA tool-kit operations. This opened a totally new vista in the field of theoretical as well as practical computing, most importantly because Adleman had demonstrated solving not something which conventional computing can easily work with but a well known hard (in fact NP complete ) problem of solving HPP. Though the instance of the problem was not large enough (a digraph with 7 vertices with known Hamiltonian path), still that was a real ground breaking idea because it opened a totally new vista of computing paradigm with lots of potential.The most prima falsi reason that DNA,RNA (Rebonuclic acid other peptide molecules have been worked upon more than any other possible alternative chemi-cal compounds is the rapid and mature advancements in the area of gene and cell Biotechnology and no mention to say that these are the technologies to work with DNA and RNA molecules. Moreover the stable and robust structure is what makes it extremely feasible to effectively work with these organic molecules.Thus to start with, in a nut shell DNA computing is - & computing with DNA strands which definitely contrasts with conventionally known computational biology (which is the study of computational tools for solving biological problems (especially related to molecular biology, see for e.g. [Waterman95]))1.1 StructureDNA molecule is a composite organic compound [AKL86) with crystalline (gives ro- bustness) and amorphic ( storage for information) structure(See Figure 1.1 and 1.2). Usually a long DNA polymer strand consists of mono structures called deoxyre- bonucleotides (or simply nucleotide or dnt ). Each nucleotide basically contains a deoryribose sugar , a chain of 5 carbon atoms (denoted) as 1' 2' 3' 4' and 5' The 3' carbon atom is associated with a hydrozyl group(OH) with one open vacancy for chemical bounding, and a phosphate group(P) which is attached with 5' atom. The l atom is connected with any one of the four nitrogenous bases (or simply bases): Adinine(A), Cytocine(C), Guanine(G), and Thymine(T). These bases characterize the whole of DNA' nucleotide. Say for example if in a dnt 1' carbon atom is at- tached with Adinine or Guanine base then the dnt is simply referred as A or G. These four nitrogenous bases are chemically classified in two groups - purines (A, G) and pirymidines (C, T). (see figure 1.1)

Comments

ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843094

Control Number

ISI-DISS-2001-78

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

http://dspace.isical.ac.in:8080/jspui/handle/10263/6250

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