Omics Database for Pathogen Gene Expression Analysis
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Solution Overview
Problem
Current methods for assessing and treating infectious diseases, particularly those caused by pathogens like C. difficile, lack effective tools for analyzing gene expression data and understanding virulence mechanisms, leading to limitations in antibiotic therapy and the emergence of resistant strains.
Innovation Solution
Development of a searchable and interactive database system that combines genomic and transcriptomic data to analyze homology, differential expression, and virulence factors of pathogenic microorganisms, enabling the identification of molecular pathways and treatment options based on gene expression analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If gene expression data from multiple sources is collected and integrated, then the comprehensiveness of pathogen analysis is improved, but the complexity of data management and analysis increases
Solution Approach 1:
The patent merges multiple disparate gene expression datasets from different sources (microarray, RNA-seq, proteomics) into a single integrated database platform. This consolidation allows comprehensive pathogen analysis while managing complexity through unified data structures and standardized access protocols, resolving the contradiction between information completeness and system complexity.
Solution Approach 2:
The database platform is designed with universal functionality to handle multiple types of omics data (transcriptomics, proteomics, metabolomics) and support various analysis methods (homology search, differential expression, pathway analysis). This multi-functional design enables comprehensive analysis across different data types without requiring separate management systems for each, thus improving comprehensiveness while controlling complexity.
2Measurement precision
If advanced bioinformatics tools are integrated into the database, then the analytical capability is improved, but the computational resources required increase
Solution Approach 1:
The system performs preliminary data processing, normalization, and quality control during data ingestion and storage. By pre-processing data before analysis requests, the system reduces the computational burden during actual queries while maintaining high analytical capability. This advance preparation resolves the contradiction between analytical precision and resource consumption.
Solution Approach 2:
The patent implements efficient data indexing and caching mechanisms that create simplified copies of frequently accessed data structures. These pre-computed indexes enable rapid queries without repeatedly processing raw data, thereby maintaining high analytical capability while significantly reducing computational resource requirements during analysis operations.
3Loss of information
If the database includes extensive genomic and transcriptomic data, then the depth of pathogen characterization is improved, but the time required for data retrieval and analysis increases
Solution Approach 1:
The database is segmented into organized modules (genomic data, transcriptomic data, proteomic data, pathway information) with hierarchical indexing. This segmentation allows the system to retrieve only relevant subsets of data for specific queries rather than scanning entire datasets, thereby maintaining deep pathogen characterization while reducing retrieval time through targeted access.
Solution Approach 2:
The patent replaces traditional sequential data search mechanisms with optimized database indexing structures and computational algorithms. This substitution enables rapid retrieval of specific genomic and transcriptomic information from extensive datasets by using index-based direct access rather than linear scanning, thus preserving data depth while minimizing retrieval time.
Data Source
AI summary
Infectious diseases pose persistent threats to the health and wellbeing of humans and animals globally. Systems and methods for multi omics-based validation of gene expression data have been developed. The methods assess disease/infection/immunity data and identify treatment regimens most likely to yield beneficial patient outcomes. The methods are implemented in a computational program for integrated, queryable pathogen/host atlas of CDC “Urgent Threat” Pathogens. Methods of treatment for disease/infection/immunity using active agents according to the described methods are also provided. In some forms, the systems and methods determine optimal treatment regimens for subjects infected with Clostridioides difficile, or Neisseria gonorrhoeae. Exemplary subjects include farm animals and humans.