Electrophoresis Data Alignment for Accurate Similarity Judgment
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Solution Overview
Problem
In electrophoresis measurements, the comparison of reference data and measurement target data is hindered by peak position shifts due to device or condition variations, making accurate identification of components challenging.
Innovation Solution
An electrophoresis measurement method that involves standardizing detected data using marker substances and then warping or shifting the measurement target data in the time axis direction to align it with the reference data, facilitating easy comparison by using cross-correlation and correlation coefficient calculations to determine optimal alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standardization is performed using marker substances to enable comparison between reference data and measurement target data, then data comparability is improved, but peak position shifts due to device or condition variations still hinder accurate component identification
Solution Approach 1:
The patent introduces an intermediary alignment process that uses correlation coefficient calculation and dynamic time warping to bridge the gap between reference data and measurement target data. This intermediary step transforms the raw electrophoresis data into aligned representations that can be reliably compared, effectively mediating between the standardized data and the goal of accurate component identification.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the time axis of the electrophoresis data through correlation-based alignment. By calculating correlation coefficients across different time shifts and applying dynamic time warping, the system transforms the temporal parameters of the data to compensate for device variations, enabling reliable comparison while maintaining measurement precision.
2Ease of manufacture
If electrophoresis measurement is performed without marker substances using methods like Dynamic Time Warping, then the measurement process is simplified, but accurate alignment and comparison of reference and measurement data becomes difficult
Solution Approach 1:
The patent applies preliminary action by performing correlation coefficient calculation and dynamic time warping alignment before the actual component identification process. This preliminary alignment step prepares the measurement data by removing time axis discrepancies, ensuring that subsequent component identification is based on accurately aligned data, thereby achieving both simplicity and precision.
Solution Approach 2:
The patent replaces the mechanical use of marker substances with a computational approach using correlation coefficient calculation and dynamic time warping. Instead of relying on physical marker peaks to align data, the system uses mathematical correlation analysis to automatically determine and apply the optimal time alignment, simplifying the measurement process while maintaining or improving alignment accuracy.
3Productivity
If reference data and measurement target data are compared directly without alignment correction, then the process is faster, but peak position shifts cause inaccurate similarity judgment
Solution Approach 1:
The patent applies partial action by implementing alignment correction only for the specific time axis discrepancies detected through correlation analysis, rather than reprocessing the entire dataset. The system calculates the optimal time shift using correlation coefficients and applies only the necessary correction, achieving accurate similarity judgment while minimizing additional processing time and maintaining productivity.
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 method allows for accurate and easy judgment of the degree of similarity between reference and measurement target data, reducing the impact of device-related shifts and improving component identification accuracy.
Implementation Method 1
a measurement target sample obtained by mixing the measurement target substance with a marker substance may be subjected to electrophoresis
Data Source
AI summary
There are provided an electrophoresis measurement method which can easily and accurately judge degree of similarity between reference data and measurement target data, a data processing device, and a data processing program. Detected data obtained by subjecting a reference sample to electrophoresis is standardized with reference to peaks of a lower limit marker substance and an upper limit marker substance, and thus reference data is acquired. Detected data obtained by subjecting a measurement target sample to electrophoresis is standardized with reference to peaks of the lower limit marker substance and the upper limit marker substance, and thus measurement target data is acquired. The measurement target data is warped or shifted in a time axis direction with reference to the reference data, and corrected measurement target data is obtained.