Mass Spectrometry Data Evaluation With Relational Vector Grouping
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Solution Overview
Problem
Biological mass spectrometry data processing is hindered by large data sizes, rigid data models, and the fragmentation of evaluation tools, making it difficult to adapt systems to new tasks and efficiently process qualitative and quantitative information on biological systems.
Innovation Solution
A data processing device with a processor unit and storage unit that allows flexible data evaluation by grouping, selecting, and modifying initial data vectors based on additional data, using a relational database to connect and store data vectors, and enabling user-defined processing steps and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional fragmented data evaluation tools are used, then existing software systems can process mass spectrometry data, but processing efficiency is low and flexibility is limited
Solution Approach 1:
The patent combines multiple fragmented data evaluation tools into a single integrated software system that can handle various mass spectrometry data types (MS, MS/MS, MSn) and analysis methods (chromatography, mobility separation, spectral analysis) within one unified platform, thereby improving both processing efficiency and analytical flexibility
Solution Approach 2:
The software system is designed with multi-functional capabilities to perform diverse operations including data acquisition, processing, visualization, and analysis of different mass spectrometry data formats and experimental designs, enabling a single system to adapt to various analytical needs without requiring separate specialized tools
2Adaptability or versatility
If existing software systems are used, then data can be processed, but the systems are rigid and cannot accommodate adaptive experimental designs
Solution Approach 1:
The software system implements dynamic configurability allowing users to adapt experimental designs and analysis parameters based on actual data characteristics and research questions. The system can dynamically adjust processing workflows, visualization options, and analysis methods without requiring rigid pre-programming, enabling flexible response to varying experimental conditions
3Measurement precision
If large data sets are processed using conventional methods, then complete analysis can be achieved, but processing time is substantial even on modern workstations
Solution Approach 1:
The software performs preliminary data processing steps including data import, formatting, and initial organization before full analysis. It implements pre-computation of spectral libraries and reference data structures that can be reused across multiple analyses, reducing redundant processing and accelerating subsequent data evaluation while maintaining complete analytical coverage
Data Source
AI summary
A data processing device comprises a processor unit adapted to process a plurality of initial data vectors provided by a chromatograph and/or a mass spectrometer, the processing being carried out in one, two or more processing steps producing items of processed data, and a storage unit adapted to save and retrieve initial data vectors and/or items of processed data, in particular processed data vectors or identified compounds, and/or items of additional data, in particular properties of the sample introduced in the mass spectrometer. Each item of processed data and/or additional data is connected to at least one initial data vector, and wherein the processor unit is adapted to group, select and/or modify initial data vectors and/or items of processed data according to one or more items of additional data.