Computer System for Microorganism Gene Identification
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Solution Overview
Problem
Current methods for developing high-productivity microorganisms, such as metabolic simulation based on flux balance analysis and keyword search devices, are insufficient in identifying effective genes for improving biological functions, leading to inefficiencies and resource wastage in genetic modification processes.
Innovation Solution
A computer system that registers design histories, searches databases for related information, computes correlations, and evaluates additional information to propose candidate genes for genetic modification, reducing the burden of searching for effective genes and optimizing microorganism development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If metabolic simulation based on flux balance analysis is used, then a solution can be obtained by multidimensional equation, but the solution may be indefinite or not analyzable and genes not included in metabolic model are not targeted
Solution Approach 1:
The patent segments the gene search process into multiple stages: first using flux balance analysis to identify candidate genes within the metabolic model, then using literature mining to find additional genes not in the model, and finally using correlation analysis to rank all candidates. This segmentation allows each method to focus on its strengths while collectively achieving comprehensive gene coverage and reliable analyzability.
Solution Approach 2:
The patent introduces literature documents as an intermediary between the metabolic model and the target gene identification. By mining literature for genes related to the target compound and the organism, the system bridges the gap between the limited metabolic model coverage and the need for comprehensive gene identification, including genes not yet incorporated into the model.
2Productivity
If keyword search device is used to search for bioitems, then a candidate bioitem can be output based on correlation score, but when biological function of high-productivity microorganism is focused on, large number of related genes are hit and effective genes cannot be narrowed down
Solution Approach 1:
The patent applies local quality by differentiating the evaluation criteria for different gene categories. Genes in the metabolic model are evaluated using flux balance analysis and correlation with target compound production, while genes from literature mining are evaluated based on their documented relationship to the target compound. This localized evaluation approach allows precise identification of effective genes within each category while maintaining overall productivity.
Solution Approach 2:
The patent changes the evaluation parameters based on the gene source and context. For genes in the metabolic model, it uses flux balance analysis parameters and correlation scores with target compound production. For genes from literature, it uses documentation relevance and experimental evidence. This parameter adaptation enables accurate identification of effective genes across diverse sources without being overwhelmed by irrelevant candidates.
3Measurement precision
If keyword search device is used to search for specific gene, then effectiveness for desired biological function cannot be searched when biological function of high-productivity microorganism is focused on
Solution Approach 1:
The patent implements a dynamic search strategy that adapts to the user's needs. When a specific gene is focused on, the system dynamically adjusts the search to evaluate that gene's effectiveness for the desired biological function using correlation analysis and flux balance analysis. When a broader search is needed, it efficiently screens multiple candidates. This dynamic approach maintains both specific gene search accuracy and overall screening efficiency.
Data Source
AI summary
A computer system that supports design for improving a function of a biological resource registers a history of the design, the history of the design including pair information of a related element related to a property of the biological resource and an operation on the related element, searches a database based on the pair information, acquires additional information other than the related element, the additional information being information related to the property of the biological resource based on a result of the search, computes a correlation of the additional information to the related element, and evaluates the additional information based on the calculated correlation.