Dissertations / Theses on the topic 'Data storage into DNA molecules'
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Berton, Chloé. "Sécurité des données stockées sur molécules d’ADN." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0431.
Full textThe volume of digital data produced worldwide every year is increasing exponentially, and current storage solutions are reaching their limits. In this context, data storage on DNA molecules holds great promise. Storing up to 10¹⁸ bytes per gram of DNA for almost no energy consumption, it has a lifespan 100 times longer than hard disks. As this storage technology is still under development, the opportunity presents itself to natively integrate data security mechanisms. This is the aim of this thesis. Our first contribution is a risk analysis of the entire storage chain, which has enabled us to identify vulnerabilities in digital and biological processes, particularly in terms of confidentiality, integrity, availability and traceability. A second contribution is the identification of elementary biological operators for simple manipulations of DNA. Using these operators, we have developed a DNACipher encryption solution that requires biomolecular decryption (DNADecipher) of the molecules before the data can be read correctly. This third contribution, based on enzymes, required the development of a coding algorithm for digital data into DNA sequences, a contribution called DSWE. This algorithm respects the constraints of biological processes (e.g. homopolymers) and our encryption solution. Our final contribution is an experimental validation of our secure storage chain. This is the first proof of concept showing that it is possible to secure this new storage medium using biomolecular manipulations
Piretti, Mattia. "Synthetic DNA as a novel data storage solution for digital images." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22028/.
Full textGermishuizen, Willem Andreas. "Dielectrophoresis as an addressing mechanism in a novel data storage system based on DNA." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615680.
Full textYanez, Ciceron. "SYNTHESIS OF NOVEL FLUORENE-BASED TWO-PHOTON ABSORBING MOLECULES AND THEIR APPLICATIONS IN OPTICAL DATA STORAGE, MICROFABRICATIO." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3573.
Full textPh.D.
Department of Chemistry
Sciences
Chemistry PhD
Camerlengo, Terry Luke. "Techniques for Storing and Processing Next-Generation DNA Sequencing Data." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1388502159.
Full textYanez, Ciceron. "Synthesis of novel fluorene-based two-photon absorbing molecules and their applications in optical data storage, microfabrication, and stimulated emission depletion." Orlando, Fla. : University of Central Florida, 2009. http://purl.fcla.edu/fcla/etd/CFE0002913.
Full textHalladjian, Sarkis. "Spatially Integrated Abstraction of Genetic Molecules." Electronic Thesis or Diss., université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG056.
Full textThe human genome consists mainly of DNA, a macromolecule consisting of a long linear sequence of bases, tightly packed to fit in the relatively small nucleus. The packing gives rise to multiple hierarchical organizational levels. Recent research has shown that, along with the linear sequence, the spatial arrangement of the genome plays an important role in the genome’s function and activity. The visualization of both linear and spatial aspects of genome data is therefore necessary. In this thesis, we focus on the concept of continuous visual abstraction for multiscale data, applied to the visualization of the human genome. Visual abstraction is a concept inspired by illustrations that makes the job of visual processing simpler, by guiding the attention of the viewer to important aspects. We first extract characteristics of multiscale data and makes a parallel comparison between genome and astronomical data. The existing differences create the need for different approaches. A common point however is the need for continuous transitions that helps viewers grasp the relationships and relative size differences between scales. To satisfy the conditions posed by the two aspects of the multiscale genome data, we present two conceptual frameworks, based on the same data. The first framework, ScaleTrotter, represents the spatial structure of the genome, on all available levels. It gives users the freedom to travel from the nucleus of a cell to the atoms of the bases, passing through the different organizational levels of the genome. To make the exploration of the structure of all levels possible, smooth temporal transitions are used. Even though all the scales are not simultaneously visible, the temporal transition used superimposes two representations of the same element at consecutive scales emphasizing their relationship. To ensure the understandability and interactivity of the data, unnecessary parts of the data are abstracted away with the use of a scale-dependent camera. The second framework, Multiscale Unfolding, focuses on aspects that are not visible in ScaleTrotter: the linear sequence and a simultaneous overview of all the organizational levels. The data is straightened to unfold the packing that occurs on several levels in a way that conserves the connectivity between the elements. To represent all the available levels, we use smooth spatial transitions between the levels. These spatial transitions are based on the same concept of the temporal transitions of the previous framework, superimposing scales and emphasizing on their relationship and size difference. We introduce an interaction technique called Multiscale Zliding that allows the exploration of the data and further emphasizes the size differences between the levels. In each framework, one of either linear of spatial aspect of genome data is sacrificed to emphasize the other. The thesis concludes with a discussion about the possibility of combining the two frameworks, minimizing the sacrifices to explore the two equally important aspects of the genome. In this thesis, we take a step closer to fully understanding the activity of the genome
Favero, Francesco. "Development of two new approaches for NGS data analysis of DNA and RNA molecules and their application in clinical and research fields." Doctoral thesis, Università del Piemonte Orientale, 2019. http://hdl.handle.net/11579/102446.
Full textBoukis, Andreas Christos [Verfasser], and M. A. R. [Akademischer Betreuer] Meier. "Moleküle als potentielle Datenspeichersysteme: Multikomponentenreaktionen sind der Schlüssel = Molecules as potential data storage systems: Multicomponent reactions are the key / Andreas Christos Boukis ; Betreuer: M. A. R. Meier." Karlsruhe : KIT-Bibliothek, 2018. http://d-nb.info/1164081071/34.
Full textPearson, Anthony Craig. "Nanoscale Surface Patterning and Applications: Using Top-Down Patterning Methods to Aid Bottom-Up Fabrication." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3757.
Full textDimopoulou, Melpomeni. "Techniques de codage pour le stockage à long terme d’images numériques dans l’ADN synthétique." Thesis, Université Côte d'Azur, 2020. http://www.theses.fr/2020COAZ4073.
Full textData explosion is one of the greatest challenges of digital evolution, causing the storage demand to grow at such a rate that it cannot compete with the actual capabilities of devices. The digital universe is forecast to grow to over 175 zettabytes by 2025 while 80% is infrequently accessed (“cold” data), yet safely archived in off-line tape drives due to security and regulatory compliance reasons. At the same time, conventional storage devices have a limited lifespan of 10 to 20 years and therefore should be frequently replaced to ensure data reliability, a process which is expensive both in terms of money and energy. Recent studies have shown that due to its biological properties, DNA is a very promising candidate for the long-term archiving of “cold” digital data for centuries or even longer under the condition that the information is encoded in a quaternary stream made up of the symbols A, T, C and G, to represent the 4 components of the DNA molecule, while also respecting some important encoding constraints. Pioneering works have proposed different algorithms for DNA coding leaving room for further improvement. In this thesis we present some novel image coding techniques for the efficient storage of digital images into DNA. We implemented a novel fixed length algorithm for the construction of a robust quaternary code that respects the biological constraints and proposed two different mapping functions to allow flexibility according to the encoding needs. Furthermore, one of the main challenges of DNA data storage being the expensive cost of DNA synthesis, we make a very first attempt to introduce controlled compression in the proposed encoding workflow. The, proposed codec is competitive compared to the state of the art. Furthermore, our end-to-end coding/decoding solution has been experimented in a wet lab experiment to prove feasibility of the theoretical study in practice
Samanta, Puspabeethi. "Coding Schemes for Secure and Reliable DNA-Based Data Storage." Thesis, 2023. https://etd.iisc.ac.in/handle/2005/6192.
Full textKumar, Praneeth V. "Exploring the Fundamental Limits of Information-Theoretically Secure Key Generation and DNA-Based Data Storage." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5956.
Full text"Medical data mining using Bayesian network and DNA sequence analysis." 2004. http://library.cuhk.edu.hk/record=b5892079.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 115-117).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iv
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Project Background --- p.1
Chapter 1.2 --- Problem Specifications --- p.3
Chapter 1.3 --- Contributions --- p.5
Chapter 1.4 --- Thesis Organization --- p.6
Chapter 2 --- Background --- p.8
Chapter 2.1 --- Medical Data Mining --- p.8
Chapter 2.1.1 --- General Information --- p.9
Chapter 2.1.2 --- Related Research --- p.10
Chapter 2.1.3 --- Characteristics and Difficulties Encountered --- p.11
Chapter 2.2 --- DNA Sequence Analysis --- p.13
Chapter 2.3 --- Hepatitis B Virus --- p.14
Chapter 2.3.1 --- Virus Characteristics --- p.15
Chapter 2.3.2 --- Important Findings on the Virus --- p.17
Chapter 2.4 --- Bayesian Network and its Classifiers --- p.17
Chapter 2.4.1 --- Formal Definition --- p.18
Chapter 2.4.2 --- Existing Learning Algorithms --- p.19
Chapter 2.4.3 --- Evolutionary Algorithms and Hybrid EP (HEP) --- p.22
Chapter 2.4.4 --- Bayesian Network Classifiers --- p.25
Chapter 2.4.5 --- Learning Algorithms for BN Classifiers --- p.32
Chapter 3 --- Bayesian Network Classifier for Clinical Data --- p.35
Chapter 3.1 --- Related Work --- p.36
Chapter 3.2 --- Proposed BN-augmented Naive Bayes Classifier (BAN) --- p.38
Chapter 3.2.1 --- Definition --- p.38
Chapter 3.2.2 --- Learning Algorithm with HEP --- p.39
Chapter 3.2.3 --- Modifications on HEP --- p.39
Chapter 3.3 --- Proposed General Bayesian Network with Markov Blan- ket (GBN) --- p.40
Chapter 3.3.1 --- Definition --- p.41
Chapter 3.3.2 --- Learning Algorithm with HEP --- p.41
Chapter 3.4 --- Findings on Bayesian Network Parameters Calculation --- p.43
Chapter 3.4.1 --- Situation and Errors --- p.43
Chapter 3.4.2 --- Proposed Solution --- p.46
Chapter 3.5 --- Performance Analysis on Proposed BN Classifier Learn- ing Algorithms --- p.47
Chapter 3.5.1 --- Experimental Methodology --- p.47
Chapter 3.5.2 --- Benchmark Data --- p.48
Chapter 3.5.3 --- Clinical Data --- p.50
Chapter 3.5.4 --- Discussion --- p.55
Chapter 3.6 --- Summary --- p.56
Chapter 4 --- Classification in DNA Analysis --- p.57
Chapter 4.1 --- Related Work --- p.58
Chapter 4.2 --- Problem Definition --- p.59
Chapter 4.3 --- Proposed Methodology Architecture --- p.60
Chapter 4.3.1 --- Overall Design --- p.60
Chapter 4.3.2 --- Important Components --- p.62
Chapter 4.4 --- Clustering --- p.63
Chapter 4.5 --- Feature Selection Algorithms --- p.65
Chapter 4.5.1 --- Information Gain --- p.66
Chapter 4.5.2 --- Other Approaches --- p.67
Chapter 4.6 --- Classification Algorithms --- p.67
Chapter 4.6.1 --- Naive Bayes Classifier --- p.68
Chapter 4.6.2 --- Decision Tree --- p.68
Chapter 4.6.3 --- Neural Networks --- p.68
Chapter 4.6.4 --- Other Approaches --- p.69
Chapter 4.7 --- Important Points on Evaluation --- p.69
Chapter 4.7.1 --- Errors --- p.70
Chapter 4.7.2 --- Independent Test --- p.70
Chapter 4.8 --- Performance Analysis on Classification of DNA Data --- p.71
Chapter 4.8.1 --- Experimental Methodology --- p.71
Chapter 4.8.2 --- Using Naive-Bayes Classifier --- p.73
Chapter 4.8.3 --- Using Decision Tree --- p.73
Chapter 4.8.4 --- Using Neural Network --- p.74
Chapter 4.8.5 --- Discussion --- p.76
Chapter 4.9 --- Summary --- p.77
Chapter 5 --- Adaptive HEP for Learning Bayesian Network Struc- ture --- p.78
Chapter 5.1 --- Background --- p.79
Chapter 5.1.1 --- Objective --- p.79
Chapter 5.1.2 --- Related Work - AEGA --- p.79
Chapter 5.2 --- Feasibility Study --- p.80
Chapter 5.3 --- Proposed A-HEP Algorithm --- p.82
Chapter 5.3.1 --- Structural Dissimilarity Comparison --- p.82
Chapter 5.3.2 --- Dynamic Population Size --- p.83
Chapter 5.4 --- Evaluation on Proposed Algorithm --- p.88
Chapter 5.4.1 --- Experimental Methodology --- p.89
Chapter 5.4.2 --- Comparison on Running Time --- p.93
Chapter 5.4.3 --- Comparison on Fitness of Final Network --- p.94
Chapter 5.4.4 --- Comparison on Similarity to the Original Network --- p.95
Chapter 5.4.5 --- Parameter Study --- p.96
Chapter 5.5 --- Applications on Medical Domain --- p.100
Chapter 5.5.1 --- Discussion --- p.100
Chapter 5.5.2 --- An Example --- p.101
Chapter 5.6 --- Summary --- p.105
Chapter 6 --- Conclusion --- p.107
Chapter 6.1 --- Summary --- p.107
Chapter 6.2 --- Future Work --- p.109
Bibliography --- p.117
Chen, Yu-Fang, and 陳玉芳. "Effect of Co-doping Lanthanoid Organometallic Compounds and Nonlinear optic organic molecules on Volume Holographic Data Storage Characteristics of Phenanthrenequinone-doped Photopolymers." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/36322721024655802263.
Full text國立交通大學
材料科學與工程學系所
101
This study describes an approach about improving the characteristics of photopolymer for holographic data storage. First of all, the diffraction efficiency (ηmax) and dynamic range (M#) of 9,10-phenanthrenequinone (PQ)–doped poly(methyl methacrylate) (PMMA) both improved significantly by co-doping five kinds of lanthanide organometallic ion lutetium (Lu3+), ytterbium (Yb3+), erbium (Er3+), neodymium (Nd3+) and cerium (Ce3+) into 9,10-phenanthrenequinone (PQ) / Poly ( hydroxyethyl methacrylate-co-methyl methacrylate) photopolymer. The diffraction efficiency and dynamic range (M #) was measured by 532nm the laser. The experimental results indicated that the performance for holographic data recording follows the order as: Lu(ac)3 > Yb(ac)3 > Er(ac)3 > PQ > Nd(ac)3 > Ce(ac)3. This order is corresponding to that of their atomic number (Lu > Yb > Er > Nd > Ce), but to the opposite order of the ionic radius(Lu+3 < Yb+3< Er+3 < Nd+3 <Ce+3) . Comparing that with the PQ singly doped P(HEMA-co-MMA) photopolymer samples, the maximal diffraction efficiency has been improved by 3.4 times to 98.3%, M/# had been improved by 2 times to 3.86, and the sensitivity was improved by 1.5 times. We also investigated the mechabism of Lu(ac)3-induced improvement in optical storage performance using FT-IR and X-ray photoelectron spectrocopyanalysis. In addition, we found that DMNA: PQ / PMMA photopolymer can be recorded by the 647nm red laser for holographic storage recording its maximum ~ 43% diffraction efficiency. A sinc-squared Bragg selection curve has been obtained and an image hologram reconstruction are also demonstrated. These experimental results support recording material for volume holographic applications in extended red spectral range.