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Our current work is developed under the query filtering approach.
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But problems were developing under the surface.
The querying algorithm used for the matching of compounds was developed by testing the query criteria used by each different existing HSQC database.
By using NoSQL database query languages like CQL (Cassandra Query Language developed to query the NoSQL database, Apache Cassandra), end users can also execute queries to update or retrieve customized information from the data storage layer through secure connections.
This entire framework is developed under open-science principles and facilitates the collaboration, refactoring, improvement and sustainability of the data, software tools, web-services and computational infrastructure developed to harvest, pre-process, munge, fuse, query, analyze and interrogate the integrated archive.
The user interface has been developed without complicated query specifications to the database.
The caTRIP team developed a distributed query engine, which was later adopted into the caGrid 1.0 toolkit as the Federated Query Processor (FQP) module.
We developed a search query for each database, and one of the 3 search-queries we set up down can be seen in Table 1.
Under this hypothesis, it is highly desirable to develop a query tool that can automatically recognize a subset of conditions under which the query gene and its targets share tightly correlated expression profiles.
In summary, we developed a model-based query algorithm based on the Bayesian model selection framework.
IF developed the web-tool to query Drosophila cell-line gene expression data.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com