1. Genome Workbench Chuong Huynh NIH/NLM/NCBI New Delhi, India
October 1, 2004
Slides from Michael Dicuccio’s Genome Workbench June 21, 2004 talk

2. Obtaining GenomeWorkbench
Not officially released to the public
Probably end of October 2004???
Beta version snapshots:
ftp://ftp.ncbi.nih.gov/toolbox/gbench/

3. NCBI Genome Workbench

4. Genome Workbench: Goals
Provide an interactive, client-side GUI
Provide full suite of annotation tools
Sequin does a lot of this
older code
primarily a submission tool
Provide a platform for visualization and analysis
Provide a platform that offers easy extensibility

5. Why Client-Side? Clients are now pretty fast Access to private data
you can actually BLAST genomes on the client-side!
Access to private data
“If you can’t bring the data to GenBank, bring GenBank to the data!”
Not just private data – extend to private data sources, data management
Ability to mix and match analytical methods

6. Application Architecture
Core application
provides application services, data management, standard dialogs and components
Plug-ins
handle most of the requests
everything is a plug-in

7. Plugin Manager

8. Core Application: MVC MVC = Model / View / Controller
30+ year old paradigm for applications
separates responsibilities of the application into discrete components
Genome Workbench uses this extensively
Model = Data being viewed
View = Viewers on this data
Controller = Application, editing framework
under construction

9. Extensibility: Plug-Ins
Framework provides standard interfaces for defining, manipulating plug-ins
Dynamically loaded at runtime; Only loaded when needed
Plug-ins live in shared libraries
can have more than one plug-in per library
Don’t need to rebuild the entire application to add new features
Three types:
Data sources, Viewers, Algorithms

10. Extensibility: Scripting
Wrap C++ interfaces with a bit of glue to make them available to scripting languages
Goals are two-fold:
obtain command console for scripting language
write plug-ins entirely in a scripting language
Focus initially on PERL, Python; intend to add others
Python completed; PERL almost completed

11. Client-Side Benefits Data Caching BLAST request caching
data in GenBank is updated, but updates for individual sequences are infrequent
Pattern of use is frequently optimal for caching
BLAST request caching
BLAST requests valid for 24 hours
IDs unique, can be cached on the client-side
Directory Indexing
can index directories of files
can search by content, molecule type, IDs, etc.

12. Some Functionality NOT Enabled
Only blastn works over the network
Choose From Other Documents Does not work in build
Access to NCBI network through a proxy