Novel Modalities in DNA Data Storage

Lim, Cheng Kai; Nirantar, Saurabh; Yew, Wen Shan; Poh, Chueh Loo

doi:10.1016/j.tibtech.2020.12.008

Cited by 31 publications

(31 citation statements)

References 97 publications

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“…The current capacity of cloud services has allowed the storage of large quantities of data about any possible phenomenon. However, as always, the quality of such data is not the best that can be achieved [1][2][3]. Thus, there is interest in improving such data [4][5][6][7], given that it is simpler to improve its quality than produce complex algorithms to handle low quality datasets.…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework for Fast Feature Selection Based on Multi-Stage Correlation Measures

Garcia-Ramirez

Calderon-Mora

Méndez-Vázquez

et al. 2022

MAKE

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Datasets with thousands of features represent a challenge for many of the existing learning methods because of the well known curse of dimensionality. Not only that, but the presence of irrelevant and redundant features on any dataset can degrade the performance of any model where training and inference is attempted. In addition, in large datasets, the manual management of features tends to be impractical. Therefore, the increasing interest of developing frameworks for the automatic discovery and removal of useless features through the literature of Machine Learning. This is the reason why, in this paper, we propose a novel framework for selecting relevant features in supervised datasets based on a cascade of methods where speed and precision are in mind. This framework consists of a novel combination of Approximated and Simulate Annealing versions of the Maximal Information Coefficient (MIC) to generalize the simple linear relation between features. This process is performed in a series of steps by applying the MIC algorithms and cutoff strategies to remove irrelevant and redundant features. The framework is also designed to achieve a balance between accuracy and speed. To test the performance of the proposed framework, a series of experiments are conducted on a large battery of datasets from SPECTF Heart to Sonar data. The results show the balance of accuracy and speed that the proposed framework can achieve.

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Section: Introductionmentioning

confidence: 99%

A Novel Framework for Fast Feature Selection Based on Multi-Stage Correlation Measures

Garcia-Ramirez

Calderon-Mora

Méndez-Vázquez

et al. 2022

MAKE

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“…Conservation of DNA, purified, in biospecimens or synthetic is a prerequisite to many applications, from biobanking, biodiversity preservation or molecular diagnostics to digital data storage (for reviews, see for instance [1][2][3]). This generates an ever-increasing number of samples which are more and more difficult and costly to store or transport.…”

Section: Introductionmentioning

confidence: 99%

Long Term Conservation of DNA at Ambient Temperature. Implications for DNA Data Storage

Coudy¹,

Colotte²,

Luis³

et al. 2022

App Cell Biol

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DNA conservation is central to many applications. This leads to an ever-increasing number of samples which are more and more difficult and costly to store or transport. A way to alleviate this problem is to develop procedures for storing samples at room temperature while maintaining their stability. A variety of commercial systems have been proposed but they fail to completely protect DNA from deleterious factors, mainly water. On the other side, Imagene company has developed a procedure for long-term conservation of biospecimen at room temperature based on the confinement of the samples under an anhydrous and anoxic atmosphere maintained inside hermetic capsules. The procedure has been validated by us and others for purified RNA, and DNA in buffy coat or white blood cells lysates, but a precise determination of purified DNA stability is still lacking. We used the Arrhenius law to determine the DNA degradation rate at room temperature. We found that extrapolation to 25°C gave a degradation rate constant equivalent to about 1 cut/century/100 000 nucleotides, a stability several orders of magnitude larger than the current commercialized processes. Such a stability is fundamental for many applications such as the preservation of very large DNA molecules (particularly interesting in the context of genome sequencing) or oligonucleotides for DNA data storage. Capsules are also well suited for this latter application because of their high capacity. One can calculate that the 64 zettabytes of data produced in 2020 could be stored, standalone, for centuries, in about 20 kg of capsules.

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“…Novel strategies, particularly DNA data storage technologies, have recently been proposed for encoding and storing data in new physical media at the molecular or atomic level [4]. DNA molecules have shown the potential of storing the encoded data in both wet and dry forms and their strands represent promising media that could preserve data due to their longevity and immense storage density [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…data in both wet and dry forms and their strands represent promising media that could preserve data due to their longevity and immense storage density [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…The workflow of the DNA storage system, as depicted in Figure 1, includes encoding the binary digital file to the sequence of four DNA bases of Adenine (A), Guanine (G), Cytosine (C), and Thymine (T), synthesizing the related information DNA (iDNA), and organizing and storing the products using a reliable physical storage system with the capability of random access to the desired sequences [7]. In order to read the information, the stored DNA oligonucleotides are sequenced using a sequencer and this is followed by an eventual decoding to obtain the initial binary codes.…”

Section: Introductionmentioning

confidence: 99%

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UV-Vis Spectrophotometric Analysis of DNA Retrieval for DNA Storage Applications

et al. 2021

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Informational Deoxyribonucleic Acid (iDNA) has gained the attention of many researchers and pioneer companies for the development of novel storage systems for the long-term and high-density storing of information. This research focuses on the physical storage of iDNA strands to address some of the current challenges by evaluating the accuracy of the process of iDNA retrieval from the surface after the dehydration process. For this aim, a UV-Vis spectrophotometric technique was used to measure the concentration of the DNA samples. Although spectroscopy has been widely employed for the evaluation of DNA concentration and contamination in a solution, it has not been used to investigate dry-state DNA, which is one of the preferred storage formats for the long-term retention of information. These results demonstrate that the UV-Vis spectrophotometric technique can be used to accurately measure dry-state DNA before the retrieval and its residues after the DNA retrieval process. This paper further examines the storage/retrieval process by investigating the relationship between the storage time and the amount of retrieved DNA or the DNA residue left on various surfaces. Based on the experimental results demonstrated and discussed in this paper, UV-Vis spectrophotometry can be used for monitoring dry-state DNA with a high accuracy larger than 98%. Moreover, these results reveal that the hydrophilicity and hydrophobicity of the surface do not significantly affect DNA retrieval over a one-month time period.

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Novel Modalities in DNA Data Storage

Cited by 31 publications

References 97 publications

A Novel Framework for Fast Feature Selection Based on Multi-Stage Correlation Measures

A Novel Framework for Fast Feature Selection Based on Multi-Stage Correlation Measures

Long Term Conservation of DNA at Ambient Temperature. Implications for DNA Data Storage

UV-Vis Spectrophotometric Analysis of DNA Retrieval for DNA Storage Applications

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