Quantum Associative Memory for DNA Sequence Search
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Solution Overview
Problem
Current methods for searching large DNA/RNA sequence databases are inefficient due to exponentially growing complexities and combinatorial explosions, leading to slow processing speeds and inability to handle vast amounts of data effectively, particularly in bioinformatics applications.
Innovation Solution
A quantum computing associative memory system that uses superpositions of wavefunctions to process multiple layers of encoded data in parallel, employing layer encoding and interference to efficiently locate matches between probe and target sequences, allowing for high-speed processing and improved resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If parallel recognition processes are used to search DNA/RNA sequences, then search speed is improved, but device complexity grows exponentially with database size
Solution Approach 1:
The patent divides the large DNA/RNA database into multiple smaller databases, each containing a subset of the total sequences. The search process is segmented into multiple stages where different processor arrays search different sub-databases in parallel. This segmentation reduces the complexity of individual processor arrays while maintaining high search speed through coordinated parallel processing across multiple arrays.
Solution Approach 2:
The patent introduces a hierarchical dimension to the search architecture by organizing processors and databases in multiple levels. Instead of a single flat parallel processing layer, the system uses multiple layers of processor arrays that can be activated selectively based on the search requirements, adding a dimensional aspect to the parallel processing structure that reduces overall complexity.
2Productivity
If existing parallel recognition processes are applied to large databases, then search capability is improved, but processing time increases due to combinatorial explosion
Solution Approach 1:
The patent performs preliminary organization of the database into structured sub-databases with predefined groupings and hierarchies before the actual search begins. This preliminary structuring allows the search process to navigate through organized subsets rather than examining all sequences randomly, significantly reducing the time required while maintaining comprehensive search capability.
Solution Approach 2:
The patent implements a continuous search mechanism where multiple processor arrays operate simultaneously and continuously on different sub-databases without idle periods. The system maintains continuous useful action by ensuring that as one processor array completes its search segment, another array is already engaged with the next segment, eliminating gaps in the search process and reducing total processing time.
Data Source
AI summary
A method for searching a database (206) with stored information using parallel searching of superposition representations of the information. In one approach, the method involves searching a target DNA or RNA genome (16) sequence to determine whether a match is present between a sequence probe and the target. The method includes encoding the target sequence as superpositions of wavefunctions, encoding the probe as one or more wavefunctions, and comparing the encoded target with the encoded probe. The encoding of the target may involve applying a transform (e.g., discrete Fourier transform) to the target sequence to obtain the wavefunctions used to form the one or more superposition representations.