Biological Data Annotation and Visualization System
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Solution Overview
Problem
The integration and analysis of diverse biological and biochemical data types, such as nucleic acid sequences, protein expressions, and cellular images, are 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 processor-based system and software tools that integrate and visualize nucleic acid sequence data, immunofluorescence, and fluorescent in situ hybridization tissue imaging measures with other data types, allowing for gene set enrichment analysis and pathway scoring, enabling interactive selection and manipulation of features on pathway views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple types of biological data (nucleic acid sequences, protein expressions, cellular images) are acquired using different processes and systems, then the amount of available information increases, but the difficulty of associating and analyzing this diverse information increases
Solution Approach 1:
The patent combines multiple types of biological data (nucleic acid sequences, protein expressions, cellular images) into a unified data structure that can be processed and analyzed together. The system integrates data from different acquisition processes and systems into a common framework, allowing simultaneous analysis of diverse information types without requiring separate processing pipelines for each data type.
Solution Approach 2:
The patent introduces an intermediary data structure and processing layer that translates and harmonizes data from different sources and formats. This intermediary layer standardizes the representation of biological data, enabling seamless integration and association of information from nucleic acid sequencing, proteomics, and imaging systems without direct complex interactions between the source systems.
2Loss of information
If comprehensive biological data is acquired from multiple sources, then the potential for insight into deregulated pathways increases, but the difficulty of parsing and associating the information increases
Solution Approach 1:
The patent segments the complex task of integrating multiple data types into distinct processing modules, each handling specific data types (nucleic acid data processing, protein expression analysis, image data handling). These segmented modules communicate through standardized interfaces, making the overall integration process more manageable and less error-prone while preserving the completeness of information from each source.
Solution Approach 2:
The patent creates a universal data processing framework that can handle multiple types of biological data through a common set of operations and algorithms. This multi-functional system performs association, analysis, and visualization tasks across different data types using unified methods, reducing the difficulty of data association while maintaining comprehensive biological insight.
3Reliability
If data from different acquisition processes is integrated, then the ability to decipher deregulated pathways improves, but the complexity of the analysis system increases
Solution Approach 1:
The patent performs preliminary processing and standardization of data from different acquisition processes before integration. Data cleaning, format normalization, and preliminary association operations are executed in advance, reducing the complexity of subsequent analysis while improving the reliability of pathway deciphering by ensuring high-quality input data for the integration system.
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
Facilitates the integration, analysis, and visualization of biological data from disparate sources, providing insights into deregulated pathways and biological states by overlaying data onto biochemical pathway maps, enhancing the understanding of complex diseases.
Implementation Method 1
nucleic acid sequence data is acquired for a portion of a tissue sample. A plurality of probes are selected based on the nucleic acid sequence data
Implementation Method 2
A plurality of immunofluorescent (IF) probes are selected based on the sequence data. One or more multiplexed images of the tissue sample are generated using the plurality of IF probes
Data Source
AI summary
Identification of regions-of-interest within cell maps is disclosed. In certain embodiments, identification of the regions-of interest is based on the use of biomarkers selected based on nucleic acid sequence data. The nucleic acid sequence data may be acquired for a homogeneous or heterogeneous set of cells present in the respective tissue sample.