Biochip Probe Pattern Learning for Low-Cost Microorganism Detection
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Solution Overview
Problem
Existing nucleic acid detection methods require unique base sequences for each probe, leading to high costs and inefficiencies in identifying microorganisms, particularly in food and beverage contamination detection.
Innovation Solution
A biochip with probes having varying base sequences detects hybridization patterns using a learning model to identify microorganisms based on probe positions, reducing the need for unique sequences and lowering costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If unique base sequences are assigned to each probe for microorganism identification, then detection accuracy is improved, but manufacturing cost and system complexity increase
Solution Approach 1:
The patent applies universality by designing a single probe structure that serves multiple functions: the same probe type can detect multiple different microorganisms by varying only the base sequence, rather than requiring unique probe structures for each organism. This reduces manufacturing complexity while maintaining detection accuracy through sequence-specific hybridization
Solution Approach 2:
The patent changes the parameter of base sequence while keeping the probe structure constant. By modifying only the nucleotide sequence parameter rather than the physical probe structure, the system achieves high detection accuracy for different microorganisms without increasing device complexity or manufacturing difficulty
2Measurement precision
If unique base sequences are assigned to each probe for microorganism identification, then detection accuracy is improved, but manufacturing cost increases
Solution Approach 1:
The patent modifies only the base sequence parameter of the probe while maintaining the same physical probe structure and manufacturing process. This approach preserves detection accuracy through sequence-specificity while significantly reducing manufacturing costs by eliminating the need to produce different probe structures for each microorganism
Solution Approach 2:
The patent uses the same probe design template (copy) for multiple microorganisms, varying only the base sequence information. This copying approach allows rapid, low-cost production of probes for different organisms using identical manufacturing processes, reducing overall manufacturing costs while maintaining detection accuracy
3Adaptability or versatility
If multiple probes with different base sequences are used, then microorganism identification capability is improved, but probe design and synthesis complexity increases
Solution Approach 1:
The patent creates a universal probe platform where a single probe design can identify multiple microorganisms by changing only the base sequence. This universal approach enhances identification capability across different organisms while simplifying probe design through standardization of the probe structure
Solution Approach 2:
The patent segments the probe functionality into two parts: a constant structural component and a variable base sequence component. This segmentation allows the structural design to be done once and reused, while only the sequence parameter needs to be customized for each target microorganism, reducing overall design complexity
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
The system efficiently identifies microorganisms by analyzing probe position patterns, reducing costs and improving accuracy in microbe detection without requiring unique probes for each organism.
Implementation Method 1
a detection unit which detects a position of a probe hybridized with a nucleic acid included in a specimen among a plurality of probes
Data Source
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AI summary
[Solution] Provided is an apparatus including: a detection unit which detects a position of a probe hybridized with a nucleic acid included in a specimen among a plurality of probes each of which being provided at a unique position within a biochip and at least some probes of which each having a base sequence different from one another; and a learning processing unit which performs a learning processing of a model which outputs a type of an organism having the nucleic acid included in the specimen in response to a pattern of the position of the probe hybridized with the nucleic acid included in the specimen being newly input, by using learning data including the pattern of the position of the probe hybridized with the nucleic acid included in the specimen and detected by the detection unit, and the type of the organism having the nucleic acid included in the specimen.