R&D: Modelling for Efficient Scientific Storage Using Simple Graphs in DNA
Compression ratios ranged from 1.18 and 1.53 and exploitation of graph-aware data ultimately helped us save substantial amount of money.
This is a Press Release edited by StorageNewsletter.com on July 17, 2024 at 2:17 pmSN Computer Science has published an article written by Asad Usmani, and Lena Wiese, Department of Computer Science, Goethe University, Frankfurt, 60325, Germany.
Abstract: “With an annual exponential growth rate, the demand for massive data archives is almost outpacing the capabilities of currently available world storage media. Alternatively, data archives could be maintained remarkably using DNA storage, making simple graph-aware data archives essential for efficiency rather than raw data. Ideally, graph-aware data archiving has a significant advantage over raw data. That helps to reduce the related data size for DNA storage in terms of nucleotides. As a result, we take advantage of lower database operational costs. Based on the Re-Pair compression technique, we provide a theoretical model for efficient scientific data storage using simple graphs in DNA. Herewith, two storage strategies – individual and composite graphs – have been investigated to discover the preferable. Some simple graph-based datasets, particularly from the biological domain, have been used to analyze experimental results. The compression ratios ranged from 1.18 and 1.53 and the exploitation of graph-aware data ultimately helped us save a substantial amount of money.“
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