Robust Composite DNA Storage under Sampling Randomness, Substitution, and Insertion-Deletion Errors

2026-02-12

AI Summary

This work addresses the insufficient reliability of composite DNA data storage under sampling randomness, base substitution, and insertion–deletion errors by formulating the problem as a polynomial channel for the first time. It introduces a three-dimensional probability simplex to represent composite nucleotide symbols, unifying this representation with a digital modulation framework. A joint error-correction mechanism is proposed, integrating LDPC channel coding, log-likelihood ratio (LLR)-based soft information processing, probability-simplex constellation mapping, and a dynamic constellation update strategy tailored to multiple error types. Experimental results demonstrate that, under existing LDPC codes, the proposed method significantly outperforms current approaches that only account for limited-magnitude probabilistic errors, thereby achieving more robust DNA-based data storage.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Data Mining & Knowledge Management: Data Compression
• Machine Learning: Probabilistic Circuits and Graphical Models

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Security and Privacy: Data transparency and provenance
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

DNA data storage offers a high-density, long-term alternative to traditional storage systems, addressing the exponential growth of digital data. Composite DNA extends this paradigm by leveraging mixtures of nucleotides to increase storage capacity beyond the four standard bases. In this work, we model composite DNA storage as a multinomial channel and draw an analogy to digital modulation by representing composite letters on the three-dimensional probability simplex. To mitigate errors caused by sampling randomness, we derive transition probabilities and log-likelihood ratios (LLRs) for each constellation point and employ practical channel codes for error correction. We then extend this framework to substitution and insertion-deletion (ID) channels, proposing constellation update rules that account for these additional impairments. Numerical results demonstrate that our approach achieves reliable performance with existing LDPC codes, compared to the prior schemes designed for limited-magnitude probability errors, whose performance degrades significantly under sampling randomness.

Problem

• composite DNA storage
• sampling randomness
• substitution errors
• insertion-deletion errors
• reliability

Innovation

• composite DNA storage
• multinomial channel
• log-likelihood ratios
• insertion-deletion errors
• LDPC codes