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bioWidgets: Visualization Components for Bioinformatics. Widgeteers. G. Christian Overton, PhD. Jonathan Crabtree, Steve Fischer, Mark Gibson. Center for Bioinformatics University of Pennsylvania. Background. No shortage of tools for genomics. Contig assemblers. Gene finders.
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Widgeteers G. Christian Overton, PhD. Jonathan Crabtree, Steve Fischer, Mark Gibson Center for Bioinformatics University of Pennsylvania
Background • No shortage of tools for genomics. • Contig assemblers. • Gene finders. • Sequence/motif search programs. • Databases galore. • Less emphasis on integrated systems and solutions, at least in the public domain. DOE-HGP: bioWidgets
Why? • Contributing factors; systems • Must be tailored to location/situation/resources. • Take more effort to build. • Require robustness. DOE-HGP: bioWidgets
A Solution • Provide components to build systems. • Initial focus on graphical user interfaces: • Data will soon be piling up. • Tools available for analysis. • The human expert is the bottleneck. • Enable visual “data-mining.” DOE-HGP: bioWidgets
bioWidget Principles • Java™ for Web distribution. • Focus on visualization. • Goals of component-based approach: • Enable software reuse. • Higher quality end result. • Promote development of standards; • Framework for communication. DOE-HGP: bioWidgets
What will be provided? • “Shrink-wrapped” applications. • Target: end-users. • Application toolkits. • Customize and build applications. • Plug-and-play model for component software. • Library routines: weight matrix, translation, etc. • Target: system builders. DOE-HGP: bioWidgets
History (abridged) • Postscript • “Doing Sequence Analysis with your Printer” • Searls, ‘93 CABIOS • Tcl/Tk and Perl/Tk bioWidgets. • bioWidgets meet Java™. DOE-HGP: bioWidgets
Current bioWidgets • Used in-house: • Sequence (DNA and polypeptide.) • Map (STS-content, radiation hybrid, etc.) • Prototype: • Chromosome. • Sequence alignment. • Multiple map. DOE-HGP: bioWidgets
Sample Applications • Examples illustrate: • What the widgets do? • What comes in (data input)? • What goes out (output)? • All can be found on-line at: • http://www.pcbi.upenn.edu DOE-HGP: bioWidgets
What comes in: GAIA • Automated annotation of “raw” sequence. • System comprised of “sensors.” • Database engine provides persistence. • Visualization: map and sequence widgets • Sharing a common data source. • Communicating selection state and position. DOE-HGP: bioWidgets
What goes out: TESS • Exporting data to external applications. • Limited by Java™ state-of-the-art. • Soon to be improved. • True “cut and paste” both between widgets and widgets and the outside world. • Support for printing. DOE-HGP: bioWidgets
BLAST Visualizations • Map: Toxoplasma gondii EST database. • (24-hour data minimart) • EST clusters fed into BLAST. • Sequence. • Standalone prototypes. DOE-HGP: bioWidgets
Architecture • Smalltalk Model-View-Controller. • Model = your hard-earned data. • View = the bioWidgets. • Controller = additional bioWidget components. • Update propagation. • Multithreaded. • Can be multidirectional. DOE-HGP: bioWidgets
Standards • OMG Life Sciences SIG (CORBAMed). • http://lsr.ebi.ac.uk • Compatibility with existing standards. • Object-oriented approach. • CORBA/RMI. • Flat-file: GCG, FASTA, etc. • Must accommodate coexisting standards. DOE-HGP: bioWidgets
JavaBeans™ • Sun’s component architecture. • Framework for generic application components. • Allows one to create and customize applications in an “application builder”. • bioWidget architecture is an extension. DOE-HGP: bioWidgets
Release Schedule • December 10: JavaBean component release. • Tutorial at NMHCC Bioinformatics conference. • “In time for the holidays.” • Why a JavaBean release? • Solves problem of customization without source code. • Strikes balance between delivering complete applications and delivering everything. DOE-HGP: bioWidgets
Related Work • bioWidget Consortium. • goodman.jax.org/projects/biowidgets/consortium/ • EBI Hyperbolic Viewer. • JADE. • GDB MapViewer. • NeoMorphic Genome Browser. DOE-HGP: bioWidgets
Future Directions • New widgets and data models. • Database schemas. • Gene expression arrays. • Pathways (metabolic, signaling, etc.) • One-to-one correspondence. • Need to speak the same language. DOE-HGP: bioWidgets
Questions? DOE-HGP: bioWidgets