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Final QMTs were stored within a SQLite reporting database.
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Orthologs and paralogs as defined by the OrthoMCL program were parsed and stored in an SQLite database using a custom schema.
Moreover, there is a SQLite database that stores user data, and which is managed by the Database Handler.
Android saves all device settings including Device ID in a SQLite database file.2 This database file can be managed by a program named sqlite3 at runtime.
After the second step, the object data set was saved as a Sqlite file which included coordinates of each object and its corresponding features in time.
Information like fasta file headers, HMM result quality, tree position and manual, tree based classification of the sequences were combined in a sqlite database [http://www.sqlite.org] that was queried to created result statistics (see Methods S5).
All this information was stored in a SQLite v3 (http://www.sqlite.org) database.
To create the database, we first stored all the evaluation information in a SQLite (http://www.sqlite.org/) database.
All results were loaded into a SQLite DB as per Trinotate instruction and results were exported into tabular format.
The identifications are parsed from mzTab files, combined and can be saved into a SQLite database for subsequent analysis.
A SQLite format database file is made available for download, which mainly contains the position frequency matrix of each motif and the datasets each motif occurs.
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