Stringomic Index Structures for Genomic Pattern Matching
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Solution Overview
Problem
Current genomics analysis algorithms fail to leverage the structural properties of genomes, such as haplotype blocks and allelic frequencies, leading to inefficient pattern matching and data processing, particularly in large-scale genomic and epigenomic data sets.
Innovation Solution
The development of index-based systems and methods that utilize a compressed data structure for stringomes, allowing for efficient pattern matching and querying directly in hardware, exploiting the structural properties of genomic data to reduce computational complexity and storage requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic stringology algorithms are used for genomics analysis, then the algorithms can be applied in the most general unconstrained setting, but they fail to take advantage of genome structure leading to prohibitively expensive computational complexity
Solution Approach 1:
The patent applies local quality by creating specialized data structures and algorithms tailored to specific genomic structures (haplotype blocks, diploid genomes, sparsity patterns) rather than using generic string matching algorithms. The system partitions the genome into local structural units and applies optimized matching techniques specific to each structure, thereby reducing overall computational complexity while maintaining versatility across different genomic analysis tasks.
Solution Approach 2:
The patent changes parameters by exploiting known genomic properties such as haplotype block boundaries, allelic frequencies, and sparsity patterns to optimize the search space and matching parameters. By adjusting algorithmic parameters based on genomic data characteristics (e.g., using population-specific reference panels, adapting to varying genome architectures), the system achieves efficient pattern matching without sacrificing adaptability to different genomic contexts.
2Ease of manufacture
If generic string matching algorithms are used without indexing structures, then the algorithms are simple to implement, but pattern matching becomes prohibitively expensive in terms of time and computational resources
Solution Approach 1:
The patent applies preliminary action by pre-processing genomic data into specialized indexing structures (such as haplotype-specific indexes, compressed genome representations, and pre-computed allele frequency tables) before pattern matching occurs. These pre-computed structures capture genomic regularities and reduce the search space, enabling fast querying without complex real-time computations. The indexing structures are built once and reused across multiple analysis tasks, dramatically improving productivity.
3Quantity of substance
If compressed data structures for stringomes are implemented, then storage requirements and computational complexity are reduced, but the system requires sophisticated indexing and pattern matching algorithms
Solution Approach 1:
The patent applies the nested doll principle by organizing genomic data into hierarchical compressed structures where genomes are partitioned into haplotype blocks, which are further subdivided into allelic variants and specific genomic features. This nested organization allows the system to store only the essential variations at each level (e.g., storing haplotype block definitions once, then storing only variant positions within blocks), dramatically reducing storage requirements. The hierarchical structure also enables efficient querying by allowing the system to navigate from coarse-grained haplotype levels to fine-grained variant levels only when necessary.
Data Source
AI summary
Exemplary systems, methods and computer-accessible mediums can receive first data related to at least one first string arranged in a directed acyclic graph, compress the first data into second data, and can search the second data for a match of at least one second string. A node of the directed acyclic graph can encode at least one substring, and an edge of the directed acyclic graph can encode instructions for concatenating substrings.