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A Tutorial on Bio-Molecular Computing

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A Tutorial on Bio-Molecular Computing BioCompT: A Tutorial on Bio-Molecular Computing A Thesis submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE In the School of Electronic and Computing Systems Of the College of Engineering and Applied Science 2012 By Kimia Karimian Bachelor of Engineering, Azad University of NajafAbad, 2005 Committee Chair: Dr. Carla Purdy Abstract DNA computing is a new and interesting development that connects computer science to molecular biology. The idea of DNA computing arose from Adleman’s 1994 experiment in which he showed how to solve the Hamiltonian path problem (HPP) in polynomial time using oligonucleotides of DNA. DNA computing enables massive parallelism at the molecular level and is one of the technologies being explored by researchers as a supplement to traditional silicon-based computing. But many computer scientists and computer engineers have little knowledge of biology and therefore find it difficult to get started in the field of DNA computing. Thus the aim of this work is to provide a tutorial to introduce DNA computing to a wider audience and to show some examples of how DNA computing can be simulated using agent-based techniques and can be applied to solve complex problems. Currently our system consists of four sections: DNA structure and behavior, basic DNA computation, DNA-based cryptography, and using agent based modeling and simulation to explore DNA behavior. We also provide a small assessment test to enable users to test themselves and evaluate their knowledge of the topics covered. The system is modular in design and can easily be modified or extended to include more information on each topic or to include additional examples of DNA computing. ii iii Acknowledgement I would like to thank Dr. Carla Purdy for her support and guidance. This work has been completed with her advice and support. I am so thankful that I had her as my advisor, who made me believe in myself and guided me through the whole process of writing my thesis. I am sure this work wouldn’t have been completed without her encouragement and understanding. I would also like to thank Dr. George Purdy and Dr. Anca Ralescu for agreeing to be in my committee. Their valuable suggestions and comments help me to improve my work. I would like to show my gratitude to my mother for her support and encouragement; she is the main reason for my success. I also want to thank my uncle for supporting me, he was the main reason that I study at university of Cincinnati. Also, I would like to thank my brother for his moral support. I dedicate my thesis to my mother. Also, I want to thank GOD for everything he has done for me. iv Table of Contents 1. INTRODUCTION………………………………………………………….……..1 1.1. Motivation………………………………………………………...…….........1 1.2. System Biology………………………………………………………….........1 1.3. Agent Based Modeling and Simulation…………………………………........2 1.4. Goal………………………………………………………………….………..2 2. BACKGROUND ……………………………………………………..………......5 2.1. Overview…………………………………………………………..……….....5 2.2. DNA Structure…………………………………………………………… .....5 2.2.1Deoxyribose Sugar……………………………………………………....6 2.2.2 Nucleotides……………………………………………………………..7 2.2.3 DNA Backbone…………………………………………………………7 2.3. Types of DNA Molecules…………………………………………………...11 2.4. Unusual Structure of DNA Molecules………………………………………12 2.5. Plasmid DNA………………………………………………………………..13 2.6. Traditional Modeling……………………………………………………......13 2.7. Agent Based Modeling and Simulation ……………………………….……14 2.8. Advantages and Disadvantages of ABMS …………………………….……15 2.8.1. Advantages of ABMS …………………………………….…………15 2.8.2. Disadvantages of ABMS ……………………………………….……15 2.9 Bio-Chemical Operations in DNA …………….……...………….………..16 2.10. DNA Computation…………………………………………………………17 2.10.1. Adleman’s Experiment ………………………………………...……18 2.10.2 DNA Complexes and Self-assembly ……………………………...…19 2.10.2.1. Grammar……………………………………………...……21 3. DESIGNS AND IMPLEMENTATION………………………………………………24 3.1. Overview………………………………..…………………..……….............24 3.2. Current System……………………………...……………………………….24 v 3.3 Existing Model of DNA Computation ………………………………………26 3.4. Advantages of DNA Computing ……………………………………………28 3.5. Disadvantages of DNA Computing ……………………………...…………29 3.6. Methods of DNA Computing ………………………….……………………29 3.6.1. Agent Oriented Method of DNA Computing ………...………………30 3.6.2. DNA Computing Based On Sticker Based Model ……………………30 3.7. DNA Cryptography………………………………………………………….31 4. BioCompT: Bio-Computing Tutorial.………………………………………………...33 4.1. Overview ……………………………………………………………………33 4.2. System Setup …………………..……………………………………………33 4.2.1. Hardware Configuration………………………………………………33 4.2.2 Software………………………………………………………………..33 4.3. GUI Design of System ……………..……………………………………….34 4.4. Use Case Diagram of System ……………………………………………….34 4.5. Biocomputing System …………………...………………………………….35 5. CONCLUSIONS AND FUTURE WORK …………...………………..……………..50 REFRENCES…………………………………………………………………………….51 vi LIST OF FIGURES Figure 2.1. DNA bases…………………………………………………………………….6 Figure 2.2. Deoxyribose sugar……...………………………………………………….…7 Figure 2.3. Nucleotide……………………………………………………………………..7 Figure 2.4. Double stranded DNA………………………...……………………….……...8 Figure2.5. Hydrogen bond……...……………………………………………...……….…9 Figure 2.6: PCR amplification……………………………………………………….…10 Figure 2.7: a) DNA hairpin, b) Plasmid DNA molecules [23], and c) DNA molecules with sticky ends……………………..……………………………….…………………..12 Figure 2.8 Hamiltonian Path Problem (HPP)…………………………...…………….…19 Figure 2.9.Some DNA complexes. Solid lines show the backbone edges and dotted line shows a pair of bases……………………………………………………………………..20 Figure 2.10. A strand, a duplex with sticky ends, a hairpin with a sticky end, and 3- branched junction……………………………………………………………………...…20 Figure 2.11. The initial complex A represented as a regular grammar…………………..22 Figure 2.12. Self-assembled DNA by context-free grammar……………………………23 Figure 2.13. Result of self-assembly by context free grammar………….………………23 Figure 4.1 Use case diagram for the bio-molecular system……………………...……...34 Figure 4.2 Start of system………………………………………………………….…….35 Figure 4.3: Overview of system ………………………………………………………...36 Figure 4.4 Inside DNA biology……………….…………………………………………37 Figure 4.5 Snapshot of agent based modeling of bio-molecular system……………...…39 Figure 4.6 DNA synthesizing……………………………………………………………40 Figure 4.7 DNA annealing…………………………………………………………….…41 Figure 4.8 DNA melting………………………………………………………………....43 Figure 4.9 Branch DNA………………………………………………………………….45 Figure 4.10 Snapshot of the system when DNA computing is selected………..………..47 Figure 4.11 DNA cryptography………………………………………………………….48 Figure 4.12 Bio-assessment test…………………………………………………………49 vii 1. INTRODUCTION 1.1. Motivation In this work we introduce our bio-computing tutorial, BioCompT. This tutorial can be used by different types of users such as scientists, engineers, and biologists. It focuses mainly on computation methods based on DNA. It does not currently cover methods based on protein signaling. We provide this system for researchers who are new to the field of bio-molecular computing and wish to learn more about different methods of DNA computing in a short period of time. In addition, we provide some background in biology for those whose knowledge of the field is small. We also discuss agent based modeling and simulation, a technique useful for studying DNA. Our system is extendable, for example, we plan in future to add more modules on DNA computation and DNA cryptography. 1.2. Systems Biology Systems biology is an emergent field with the aim of system level understanding of biological systems [2]. System level understanding of a biological system can be divided into four areas: 1) System structure: this includes gene regulation and biochemical networks, as well as physical structures. 2) System dynamics: this includes quantitative and qualitative analysis of the system, and construction of theoretical models. 1 3) Control methods: control of the state of the cell; the state can be measured to minimize malfunction and provide potential therapeutic targets for treatment of disease [1]. 4) Design methodogy: using definite design principles and simulation, construct a biological system [1]. 1.3. Agent Based Modeling and Simulation (ABMS) Agent Based Modeling and Simulation (ABMS) is a powerful simulation and modeling technique for simulating actions and interactions of autonomous agents. ABMS models and simulates the behavior of the system using the bottom-up approach. In ABMS, a system is modeled as a collection of autonomous decision- making entities called agents. Each agent individually assesses its situation and makes decisions based on its set of rules [2]. Even a simple ABMS can exhibit complex behavior patterns and provide valuable information about the dynamics of the real world system that it emulates. It should be mentioned that agents might be capable of evolving, allowing unanticipated behaviors to emerge [2]. 1.4. Goal Our goal is to provide a practical tutorial for users from different backgrounds who are new to the field of bio-molecular computation. An additional goal is to ensure that this system can be extended in future. Examples we provide in this tutorial include: 2 • Simulation of self-assembled molecules, and demonstration of some DNA behaviors. • Brief overview of DNA biology for engineers and computer scientists who are using this system to learn about bio-molecular computing models. • Examples of agent based modeling of DNA behavior. This thesis is organized
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