Compressed Sensing for In Situ Gene Imaging
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Solution Overview
Problem
Current methods for imaging genes in situ are limited by their ability to profile only a small number of genes at a time, making it difficult to understand complex cell and tissue systems, particularly in the context of tumor evolution and disease, where spatial profiling of protein/mRNA abundance is needed without requiring extensive data acquisition and manipulation.
Innovation Solution
The method involves detecting composite genes through single cell sequencing, forming gene modules, and using compressed sensing to decompress images of individual genes from composite images, allowing for the imaging of multiple genes simultaneously and reconstructing gene expression patterns in situ.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional in situ imaging methods are used to profile genes, then spatial distribution information is obtained, but only a small number of genes can be profiled at a time
Solution Approach 1:
The patent combines multiple gene imaging channels into a single composite image by merging fluorescent signals from multiple genes. This allows simultaneous profiling of many genes (increasing quantity) while using a unified imaging approach that reduces overall system complexity
Solution Approach 2:
The composite imaging system serves multiple functions: it captures spatial distribution information for numerous genes simultaneously, enables downstream computational decomposition, and provides a universal platform for studying complex biological systems like tumor ecosystems without requiring separate imaging systems for each gene
2Productivity
If composite gene imaging is used to increase gene profiling capacity, then multiple genes can be analyzed simultaneously, but the complexity of data manipulation increases
Solution Approach 1:
The patent performs preliminary computational decomposition of composite images into individual gene expression patterns before final analysis. By pre-processing the composite data to separate individual gene signals, the system increases profiling throughput while managing data processing complexity through structured computational steps
Solution Approach 2:
The composite image serves as an intermediary representation that encodes information from multiple genes. This intermediate form allows efficient data storage and transmission, with computational algorithms acting as mediators to decode the composite signal into individual gene expressions, thereby increasing throughput while systematically handling processing complexity
3Loss of information
If single cell sequencing is performed to identify gene modules, then comprehensive gene expression data is collected, but extensive data acquisition and manipulation is required
Solution Approach 1:
The patent extracts key gene module activities from comprehensive single-cell sequencing data and represents them as a smaller set of composite genes. This extraction process preserves essential gene expression information while reducing data dimensionality, thereby maintaining information completeness while significantly reducing processing time
Data Source
AI summary
The present invention relates to tissue and cell imaging utilizing genomic informatics and gene-expression profiling. Gene-expression profiles utilized in methods to obtain in situ imaging of cells and tissues provide complex molecular fingerprints regarding the relative state of a cell or tissue.