Dynamic Pathway Map Linking for Spatial Biological Data
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Solution Overview
Problem
The integration and analysis of diverse biological and biochemical data from disparate sources, such as protein and nucleic acid sequences, cellular data, and images, is challenging due to the use of different processes and systems, making it difficult to decipher deregulated pathways and biological states in complex diseases.
Innovation Solution
A computer-based method and processor-based system that displays pathway maps linked to nucleic acid sequence data and cell maps, allowing interactive evaluation and integration of biomarker expression data, enabling the highlighting of cells and setting node values or states based on user inputs, and facilitating gene set enrichment analysis and pathway scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple types of biological data (protein expression, nucleic acid sequences, cellular data, images) are acquired from different sources and processes, then the quantity and diversity of information increases, but the difficulty of integrating and associating this information increases
Solution Approach 1:
The patent merges multiple types of biological data (protein expression data, nucleic acid sequence data, cellular data, and images) into a single integrated system that allows simultaneous visualization and analysis. The system combines data from different sources and processes into unified pathway maps and cell maps, enabling researchers to analyze all data types together rather than separately.
Solution Approach 2:
The patent introduces pathway maps as an intermediary layer that connects and associates different types of biological data. The pathway maps serve as a mediator that links protein expression data, nucleic acid sequences, and cellular images through known biological pathways, making it easier to associate disparate information without requiring direct integration of all data sources.
2Ease of manufacture
If conventional data acquisition and analysis tools are used to analyze complex diseases, then standard analysis procedures can be applied, but the ability to decipher deregulated pathways and biological states remains challenging
Solution Approach 1:
The patent adds a new dimension to data analysis by integrating spatial information from tissue images with molecular data from pathways. The system displays cell maps with spatial coordinates alongside pathway maps, allowing analysis that combines both the spatial organization of cells and their molecular pathway activities, thereby improving the reliability of deciphering disease mechanisms.
Solution Approach 2:
The patent creates a multi-functional analysis system that can simultaneously perform multiple types of analysis: pathway enrichment analysis, spatial cell distribution analysis, correlation analysis between different data types, and interactive exploration. This universal system handles diverse analysis needs within a single platform, improving both ease of use and reliability.
3Loss of information
If there is a large number of molecule types and their concentrations in different cells and sub-cellular compartments, then comprehensive biological information is available, but the difficulty of associating and analyzing this data increases
Solution Approach 1:
The patent segments the complex biological data into distinct organizational layers: pathway maps for molecular interactions, cell maps for cellular-level data with spatial information, and tissue images for contextual information. This segmentation allows the system to handle large numbers of molecule types and concentrations by organizing them into manageable, visually distinct components that can be associated through their spatial and functional relationships.
Data Source
AI summary
Dynamic linking of pathway maps and cell maps is disclosed in certain embodiments. In such embodiments, the pathway maps are linked to spatially-localized regional nucleic acid data (e.g., sequence data), as opposed to non-spatially selected nucleic acid data. The pathway map and cell map data may be linked so that interactions results in changes or updates to the linked map, such as the selection or highlighting of cells exhibiting pathway map characteristics specified by a user of updating of node values or states to correspond to that of a cell or cells selected by the user.