DNA Storage Encoding Rule Generation via Directed Graph Optimization
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Solution Overview
Problem
Existing DNA storage encoding/decoding algorithms cannot completely avoid extreme GC content and special motifs, leading to high error rates in third-generation sequencing, which hinders the wide application of DNA storage technology.
Innovation Solution
A method involving a sliding window approach to generate a DNA storage encoding/decoding rule, where a directed graph is used to connect qualified sequences, delete nodes with low or excessive out-degrees, and apply specific limiting conditions to optimize encoding efficiency, resulting in an end-to-end direct mapping between binary and base sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed rules are used for DNA storage encoding/decoding, then the encoding process is simple, but extreme GC content and special motifs cannot be completely avoided, leading to high error rates in third-generation sequencing
Solution Approach 1:
The patent applies dynamics by transitioning from fixed encoding rules to a dynamic graph-based encoding system. The directed graph allows the encoding process to adaptively select sequences based on current constraints and objectives, enabling real-time optimization of GC content distribution and motif avoidance while maintaining encoding functionality.
Solution Approach 2:
The patent utilizes parameter changes by adjusting multiple sequence characteristics simultaneously - GC content, motif composition, and sequence structure - through the graph-based optimization process. This multi-parameter optimization enables avoidance of extreme values and special motifs that cause sequencing errors, while the encoding remains computationally feasible.
2Speed
If third-generation sequencing is used for fast DNA storage reading, then sequencing speed is improved, but error rate increases due to inability to handle extreme GC content and special motifs
Solution Approach 1:
The patent applies preliminary anti-action by pre-processing the encoding to prevent the formation of extreme GC content and special motifs before sequencing occurs. The graph-based encoding system proactively avoids creating problematic sequences, thereby counteracting the high error rate tendency of third-generation sequencing technology.
Solution Approach 2:
The patent implements feedback mechanisms where the encoding process continuously monitors and adjusts sequence generation based on GC content distribution and motif analysis. This feedback loop ensures that generated sequences remain within optimal ranges for third-generation sequencing accuracy, allowing fast reading while maintaining reliability.
3Productivity
If existing encoding algorithms are used, then encoding density can be increased, but extreme GC content and special motifs still occur, requiring additional error correction computing time
Solution Approach 1:
The patent applies preliminary action by incorporating error prevention directly into the encoding process itself. The graph-based system pre-prevents the generation of sequences that would require error correction, eliminating the need for subsequent computational error correction steps and reducing overall processing time while maintaining high encoding density.
Solution Approach 2:
The patent converts the potential harm of sequence generation constraints into a benefit by using the directed graph to systematically explore and select optimal sequences. The constraints that would normally limit encoding density are transformed into guiding principles that produce sequences inherently suitable for fast sequencing, thereby reducing error correction needs.
Data Source
AI summary
A method for generating a DNA storage encoding/decoding rule, and a method for DNA storage encoding/decoding. The method for generating the DNA storage encoding/decoding rule includes: setting a sliding window for the DNA storage encoding/decoding rule; screening out, from a full set of sequences, a set of qualified sequences complying with a limiting condition; connecting the sequences in the set of qualified sequences by means of a directed graph; deleting, in the directed graph, nodes of which the number of out-degree is less than a set threshold for the number of out-degree; deleting excess out-degree of each node in the directed graph; and acquiring an algorithm chart, which includes the DNA storage encoding/decoding rule.