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Oracle BLAST Demonstration
This demonstration provides a browser interface for multiple (blastall)
BLASTP protein vs. protein sequence searches for the Swiss-Prot/UniProt
database. Target and query sequence lists can be selected based on annotation
metadata. The demonstration can be expanded to utilize additional protein sequence databases.
This demonstration requires the apache web server and the Oracle 10gR2 database.
Download File (Zip, 50KB) |
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Semantic Technologies Code Samples
Sample Oracle RDF Plugin for Protege
- This Oracle RDF plugin will help Protege users to understand how to make calls to the Oracle Database to read and write RDF data. |
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Oracle Data Mining Option BLAST
Demonstration
The Basic Local Alignment Search Tool (BLAST) is a widely used
sequence similarity search and alignment algorithm for bioinformatics.
This code demonstrates the Oracle Data Mining Option's support of the BLAST
algorithm. The example includes a significant data set to illustrate the code, so
the download file is large. To use the sample code, the Oracle Data Mining Option
must be installed.
Download File (Zip, 17MB) |
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Cytoscape Plugin
This code enables users to visualize and analyze network data stored in Oracle Spatial Network Data Model using Cytoscape. In order to use the plugin, users need to install Oracle Database 10g with the Spatial option, and Cytoscape. Both
Plugin File version 1.0 (Zip, 2.4MB) and
Plugin File version 1.1 (Zip, 2.4MB) work with Cytoscape versions 2.0 and 2.1.
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Latest
Version! - Nov '05 - MEDLINE Text
Mining Demonstration
These are the code and data files for the MEDLINE Text Mining demonstration
presented at the Oracle Life Sciences User Group meeting in Boston, May 16th, 2005. The
code is compatible with Oracle Database 10g Release 2.
For a tutorial, see OracleTextMiningWorkflow.pdf within the code file.
Code
(Zip, 4MB)
Sample Data (Zip, 4 MB)
Large Sample Data Set (Zip, 24 MB) |
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Oracle Text Sample Application (Yapa)
Yapa is a sample application that demonstrates
the main features of Oracle Text including categorization, clustering, and visualization.
Scientific American Medicine literature was used in the demo.
Introduction
Screen Shots |
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