Scalable large-scale biomedical sample management and visualization platform
A biomedical, large-scale technology, applied in the field of biology or medicine, can solve the problems of not being able to freely select search items and search forms, providing search sample results for those who cannot, and being difficult to meet the various needs of users, achieving convenient distributed The expansion of deployment and storage, the realization of statistics and visualization, the effect of fast operation
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specific Embodiment 1
[0027] An expandable large-scale biomedical sample management and visualization platform is characterized in that: the platform includes a sample statistics module, a visualization module, a retrieval module and a mongodb database, and the platform is connected to the mongodb database.
[0028] The platform uses a non-relational database mongodb to be responsible for data storage and management, and mongodb is responsible for adding new sample data and other operations. According to the current demand, there is only one database server in the cluster. In the future, the number of database servers in the cluster can be further increased to expand data storage according to the increase in data volume and the improvement of operating efficiency requirements. At the same time, further data backup and load balancing can be performed. Further improve system reliability and availability.
[0029] The platform enables quality control of samples. In the process of sample storage, the ...
specific Embodiment 2
[0033] A scalable large-scale biomedical sample management and visualization platform operation method, comprising the following steps:
[0034] Step 1: The user logs in to the scalable large-scale biomedical sample management and visualization platform for identity and authority verification;
[0035] Step 2: After the user completes the authority verification, the user adds data information to the platform and uploads it;
[0036] Step 3: Perform quality inspection on the added data information, the data information that fails the quality inspection is not stored in the mongodb database and returned to the customer to correct the error, and the data information that passes the quality inspection is stored in the mongodb database;
[0037] Step 4: The user comprehensively searches the sample information in the mongodb database through multiple conditions, and checks the statistics of the search results.
[0038] Step 5: After the retrieval is completed, the scalable large-sc...
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