Biological Image and Sequence Integration System
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Solution Overview
Problem
Existing databases face difficulties in effectively utilizing nucleotide sequence information for organism identification and classification, as it is challenging to associate and register biological images with corresponding nucleotide sequence data.
Innovation Solution
An integration system that combines biological image acquisition, nucleotide sequence information acquisition, and data association, using devices to register biological images and nucleotide sequence information in an integrated database, allowing for easier identification and classification of organisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If nucleotide sequence information is registered in databases individually, then the information can be acquired, but it is difficult to use for identification and classification
Solution Approach 1:
The patent combines biological image data and nucleotide sequence information into an integrated database structure, where images and sequences are associated through common identifiers. This merging allows users to simultaneously access visual and molecular data for comprehensive organism identification and classification, resolving the contradiction between information availability and usability.
Solution Approach 2:
The patent introduces an integration system that acts as an intermediary between image databases and sequence databases. This system associates images with nucleotide sequences through matching algorithms and common identifiers, enabling users to query either type of data and receive integrated results, thereby improving ease of operation while preserving information availability.
2Ease of operation
If biological images and nucleotide sequence information are associated and registered in an integrated database, then ease of use for identification and classification is improved, but device complexity increases
Solution Approach 1:
The integration system is divided into separate functional modules: an image acquisition module, a sequence acquisition module, and an association module. Each module handles specific tasks independently, and they are connected through standardized data interfaces. This segmentation reduces overall system complexity while enabling integrated functionality for improved ease of use.
Solution Approach 2:
The integration system is designed with universal interfaces and data structures that can handle multiple types of biological data (images, sequences, metadata) through a common framework. This multi-functionality approach allows the system to perform various operations (storage, retrieval, association, query) without requiring separate specialized systems, thereby managing complexity while improving ease of operation.
Data Source
AI summary
An integration system comprising a biological image acquiring device which acquires, from a sample including biological particles which are a detection target, a biological image which is an image of the biological particles; a nucleotide sequence information acquiring device which acquires nucleotide sequence information of the biological particles; and an integration device which associates and registers the biological image and the nucleotide sequence information acquired from the same type of biological particles in an integrated database.