Oligonucleotide Selection via Linear Programming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for detecting pathogens with genetic diversity are inefficient and inaccurate due to the need for extensive manual or empirical selection of oligonucleotide combinations to achieve optimal coverage of target nucleic acid sequences, particularly when dealing with a large number of sequences or requiring high target coverage with a limited number of probes.
Innovation Solution
The development of optimization logic using linear programming to select an optimal combination of oligonucleotides that can detect multiple target nucleic acid sequences with a desired coverage, select target sequences for multiplex detection with the highest coverage using a limited number of oligonucleotides, and determine conserved regions within these sequences, thereby improving speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional manual or empirical methods are used to select oligonucleotide combinations, then the process can be performed with simple procedures, but the speed and accuracy of detection are reduced due to time-consuming selection processes
Solution Approach 1:
The patent replaces manual/empirical selection methods with computational algorithms that automatically determine optimal oligonucleotide combinations. The system uses computer-based optimization to select probe sets, eliminating time-consuming manual procedures while maintaining detection accuracy.
Solution Approach 2:
The system performs self-optimization by automatically evaluating multiple oligonucleotide combinations and selecting the optimal set without human intervention. The algorithm independently determines the best probe combinations based on predefined criteria, reducing both time loss and improving productivity.
2Measurement precision
If a large number of oligonucleotide combinations are manually evaluated to ensure comprehensive coverage, then detection accuracy improves, but the complexity and time required for analysis increases significantly
Solution Approach 1:
The patent replaces complex manual evaluation processes with computational algorithms that systematically assess oligonucleotide combinations. The computer-based system evaluates coverage, specificity, and other parameters automatically, maintaining high accuracy while reducing operational complexity.
Solution Approach 2:
The optimization algorithm serves multiple functions simultaneously: it evaluates coverage of target sequences, assesses probe specificity, determines optimal combinations, and validates detection parameters. This multi-functionality reduces overall system complexity while maintaining comprehensive accuracy.
3Reliability
If probes are designed to cover all known nucleic acid sequences of a pathogen with genetic diversity, then detection reliability improves, but the number of probes required increases
Solution Approach 1:
The optimization algorithm automatically identifies the minimal set of probes needed to achieve comprehensive coverage. By self-evaluating combinations, the system determines the optimal number and selection of probes, reducing quantity while maintaining reliability through computational optimization.
Solution Approach 2:
The system changes the approach from designing probes to cover all sequences individually to using an optimization algorithm that selects the minimal effective combination. By altering the selection criteria and evaluation parameters, the system achieves comprehensive coverage with fewer probes, improving reliability while reducing quantity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables rapid and accurate detection of target nucleic acid sequences with improved speed and accuracy, effectively addressing the inefficiencies of conventional methods by automating the selection of oligonucleotide combinations and identifying conserved regions for enhanced genetic diversity detection.
Implementation Method 1
Most of the molecular diagnostic techniques use oligonucleotides such as primers and probes hybridizable with target nucleic acid molecules
Data Source
AI summary
The present invention relates to optimization logic for preparing an optimal combination of oligonucleotides hybridized with a plurality of target nucleic acid sequences, in a completely different approach from conventional methods, i.e., empirical and manual methods. In addition, the optimization logic of the present invention may be used to (i) preparing an oligonucleotide combination used to detect a plurality of target nucleic acid sequences with a target coverage of interest, (ii) selecting target nucleic acid sequences to be detected by a multiplex target detection with a highest target coverage by using a limited number of oligonucleotides, and (iii) determining a conserved region in a plurality of target nucleic acid sequences.