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Reconstruction algorithms for DNA-storage systems.

Omer Sabary1, Alexander Yucovich2, Guy Shapira2

  • 1The Henry and Marilyn Taub Faculty of Computer Science, Technion, 3200003, Haifa, Israel. Omersabary@cs.technion.ac.il.

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Summary
This summary is machine-generated.

New DNA reconstruction algorithms improve data recovery accuracy in DNA storage systems. These methods use dynamic programming to minimize errors, outperforming previous approaches even with high error rates.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Storage

Background:

  • DNA storage systems offer high-density data archival.
  • DNA synthesis and sequencing are prone to errors (deletions, insertions, substitutions).
  • Accurate reconstruction of original DNA sequences from noisy data is crucial for DNA storage viability.

Purpose of the Study:

  • To develop novel algorithms for the DNA reconstruction problem.
  • To minimize the edit distance between original and reconstructed DNA sequences.
  • To improve the accuracy of DNA data recovery from noisy traces.

Main Methods:

  • Global analysis of multiple noisy DNA sequence copies (traces).
  • Application of dynamic programming algorithms, specifically shortest common supersequence and longest common subsequence.
  • Development of new DNA reconstruction algorithms without limitations on input size or trace number.

Main Results:

  • New algorithms demonstrate superior reconstruction accuracy compared to existing methods.
  • Effective performance observed even with high error probabilities (up to 0.27).
  • Validation on simulated, experimental, and synthesized DNA datasets.

Conclusions:

  • The developed algorithms significantly enhance DNA sequence reconstruction accuracy.
  • These advancements are vital for the practical implementation of reliable DNA data storage.
  • The algorithms provide a robust solution for handling errors in DNA storage channels.