Genomic Data Encoding Using Sourceblocks for Bandwidth Limits
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Solution Overview
Problem
The rapid growth of data storage demand, particularly with genomic data, outpaces current storage capacity and transmission bandwidth, and existing encryption technologies are vulnerable to quantum computing, necessitating an efficient and secure method for encoding, storing, and transmitting genomic and bioinformatic datasets.
Innovation Solution
A system and method for bandwidth-efficient encoding of genomic data using a sequence analyzer to deconstruct datasets into sourceblocks, assign reference codes, and manage these blocks through a data deconstruction engine and library management module, enabling secure and compact data storage and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is used to increase storage capacity, then storage efficiency improves, but data loss occurs with lossy compression or limited gains with lossless compression
Solution Approach 1:
The patent segments genomic data into fixed-size blocks and processes each block independently through cryptographic transformation. This segmentation allows the system to achieve significant compression ratios while maintaining complete data integrity, as each block can be uniquely reconstructed from its transformed representation without loss of information.
Solution Approach 2:
The system transforms data from one parameter space to another through cryptographic encoding, changing the representation of genomic data without losing information. The transformation alters the parameter values while preserving the underlying data structure, enabling compression while preventing data loss through the mathematical properties of the transformation.
2Quantity of substance
If physical storage capacity is increased to meet demand, then storage availability improves, but manufacturing capacity constraints prevent solving the problem
Solution Approach 1:
By segmenting data into transformable blocks, the system reduces the physical storage capacity needed while maintaining full data availability. The segmentation enables efficient use of existing storage infrastructure without requiring additional manufacturing capacity.
Solution Approach 2:
The system creates transformed copies of the original data that occupy less physical space but contain all necessary information for reconstruction. These cryptographic copies replace the need for additional physical storage capacity, avoiding manufacturing constraints.
3Speed
If transmission bandwidth is increased to handle large datasets, then data transmission speed improves, but bandwidth limitations constrain networked computing applications
Solution Approach 1:
The patent segments genomic data into smaller transformable blocks that can be transmitted more efficiently through available bandwidth. This segmentation reduces the total transmission volume while maintaining data completeness, enabling faster transmission speeds without requiring additional bandwidth infrastructure.
Solution Approach 2:
By transforming data parameters through cryptographic encoding, the system reduces the effective data size that must be transmitted. This parameter transformation enables faster transmission speeds within existing bandwidth constraints, removing limitations on networked computing applications.
4Reliability
If existing encryption technologies are used to protect data, then data security improves, but quantum computing threatens to compromise security
Solution Approach 1:
The system employs cryptographic transformations that operate in a different parameter space than traditional encryption, changing the mathematical foundation of security. This parameter change creates security mechanisms that are resistant to quantum computing attacks while maintaining strong data protection.
Solution Approach 2:
The patent creates cryptographic copies of data through block transformation that provide security without relying on traditional encryption algorithms vulnerable to quantum attacks. These transformed copies maintain data security through mathematical properties that are quantum-resistant.
Data Source
AI summary
A system and methods for bandwidth-efficient encoding of genome and bioinformatic sequence datasets comprising a sequence analyzer configured to: analyze a received sequence dataset to determine a sequence dataset file type, scan the sequence dataset to maintain a count of unique characters contained therein, identify positions where the unique character count increases by a power of two, deconstruct the sequence dataset into a plurality of sourceblocks at the identified positions, and encode the plurality of sourceblocks using a data deconstruction engine and library management module to assign each sourceblock a reference code.