Sequence Matching with Error Tolerance via Sub-fragment Segmentation
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Solution Overview
Problem
Current algorithms for matching genetic sequence fragments against large target sequences are computationally intensive and inefficient, particularly when allowing for 1 or 2 errors, due to the high number of fragments generated in biotechnology applications like drug discovery and disease analysis.
Innovation Solution
The method involves breaking test fragments into E+1 sub-fragments and using an index of sub-sequences to quickly determine exact matches, reducing computational complexity by only comparing non-matching sub-fragments to adjacent portions of the target sequence, thereby terminating unnecessary matching operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If BLAST algorithms are used to perform fragment matching while allowing for errors, then matching accuracy is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The test fragment is divided into multiple sub-fragments (e.g., 3 sub-fragments for E=2 errors). Each sub-fragment is independently matched against the target sequence using exact matching. This segmentation reduces the computational complexity from comparing the entire fragment with all possible error combinations to performing multiple simpler exact matches on smaller sub-fragments.
Solution Approach 2:
The target sequence is pre-processed to create an index data structure (such as a suffix array, hash table, or other efficient indexing structure) that enables rapid exact matching. This preliminary action allows the matching phase to quickly locate potential matches without performing comprehensive error-tolerant comparisons against the entire target sequence.
2Reliability
If comprehensive error-tolerant matching is performed on all fragments, then matching reliability is improved, but processing time increases to hours or days
Solution Approach 1:
By segmenting the fragment into sub-fragments and performing exact matching on each, the method reliably identifies matches with up to E errors while avoiding the time-consuming exhaustive search of all possible error combinations. The segmentation enables parallel processing and reduces the search space significantly.
Solution Approach 2:
The approach uses multiple copies of the fragment broken into sub-fragments that are independently matched. This copying strategy allows simultaneous processing of multiple sub-fragments, reducing overall processing time while maintaining reliability through the aggregation of match results.
3Measurement precision
If in-memory analysis is used for fragment matching, then matching precision is improved, but resource consumption and computational load increase
Solution Approach 1:
Segmenting the matching task into independent sub-fragment comparisons reduces the computational energy required for each comparison. Exact matching on small sub-fragments consumes significantly less energy than error-tolerant matching on the entire fragment, while the segmented approach maintains overall matching precision.
Solution Approach 2:
The method extracts only the essential matching information from each sub-fragment comparison and aggregates these results to determine overall fragment matches. This extraction approach avoids the energy-intensive process of evaluating all possible error combinations while preserving matching precision.
Data Source
AI summary
Systems, methods, and other embodiments associated with sequence matching with no more than a number E errors are disclosed. A test fragment to be located within a target sequence with at most a number E errors is received. The test fragment is broken into E+1 test sub-fragments. If one test sub-fragment is located within the target sequence with no errors; a determination is made as to whether the other test sub-fragments are located within the target sequence adjacent to the one test sub-fragment with a total of at most E errors. If the other test sub-fragments are located within the target sequence adjacent the one test sub-fragment with at most E errors, a location of the test fragment within the target sequence is returned.