Microorganism Characterization via DNA Sequence Segmentation
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Solution Overview
Problem
Current systems for characterizing microorganisms are inefficient, requiring significant processing time and unable to identify microorganisms without prior database information, making them impractical for clinical applications.
Innovation Solution
The system characterizes microorganisms by segmenting digital DNA sequences, performing alignments with multiple databases, and generating reports for treatment suggestions, allowing for rapid identification of multiple microorganisms simultaneously using techniques like BLAST and iterative comparison window adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current microorganism characterization systems are used, then microorganisms can be identified, but the processing time is too long (several days) for clinical applications
Solution Approach 1:
The patent segments the DNA sequence analysis into multiple independent alignment tasks that can be performed in parallel. The sequence is divided into multiple regions, and each region is aligned against databases simultaneously using separate computational threads or processors, dramatically reducing the total processing time while maintaining identification accuracy.
Solution Approach 2:
The system performs preliminary actions by pre-processing and organizing database sequences into optimized formats before the actual alignment process. Indexing and preprocessing steps are completed in advance, allowing the main analysis to proceed faster without compromising the ability to accurately identify microorganisms.
2Measurement precision
If current systems characterize microorganisms, then identification results are obtained, but additional software and specially trained researchers are needed to interpret results and determine treatment
Solution Approach 1:
The system integrates multiple functions into a single platform: it performs sequence alignment, identifies microorganisms, retrieves treatment information from databases, and generates clinically actionable reports all in one process. This multi-functional approach eliminates the need for separate interpretation software and makes the system usable by clinicians without specialized bioinformatics training.
Solution Approach 2:
The system automatically performs the interpretation of alignment results and treatment recommendation generation without requiring manual intervention from researchers. The software self-service includes automatic threshold determination, result validation, and treatment protocol retrieval, making the entire process accessible to clinicians rather than requiring specialized personnel.
3Measurement precision
If current systems identify microorganisms, then database information is utilized, but microorganisms without prior database information cannot be identified
Solution Approach 1:
The system performs partial alignment matches rather than requiring complete sequence matches. By allowing identification based on partial sequence homology and using iterative refinement of alignment parameters, the system can identify novel microorganisms that share partial similarity with known sequences in the database, extending its versatility beyond exactly matched organisms.
4Productivity
If parallel processing of multiple microorganisms is implemented, then identification time is reduced, but computational resources and system complexity increase
Solution Approach 1:
The system segments both the computational tasks and the data structures to enable efficient parallel processing. By dividing the analysis into independent modular units that can run simultaneously while sharing common resources through standardized interfaces, the system achieves high productivity without proportionally increasing overall system complexity.
Data Source
AI summary
Systems and methods to characterize one or more microorganisms or DNA fragments thereof are disclosed. Exemplary methods and systems use comparison of DNA sequencing information to information in one or more databases to characterize the one or more microorganism or DNA fragments thereof. Exemplary systems and methods can be used in a clinical setting to provide rapid analysis of microorganisms that may be a cause of infection.