1. CICC June meeting IUPUI team: Kelsey Forsythe Malika Mahoui Deepthi Jonnala Usha Cheemakurthi

2. Outline Distributed Drug Discovery project Adopting Biofacets for Chemical Informatics Workflow automation

3. Adopting Biofacets for Chemical Informatics What is Biofacets? –Faceted based integration system for biological databases –Features a meta-search engine that target variegated biological databases –Supported by a set of biological facets used to dynamically categorize query results facilitating results browsing and query refinement

4. Adopting Biofacets for Chemical Informatics Biofacets variations –As a Web server integrating a diversified set of biological databases and a rich set of facets (http://biofacets.informatics.iupui.edu:8080/biofac ets/)http://biofacets.informatics.iupui.edu:8080/biofac ets/ –A framework to be used for generating custom versions; with user specific collection of scientific databases and facets –Chemical informatics version: currently being developed by Usha Cheemakurthi

5. Workflow automation Problem statement: –Workflow environments such as Taverna are too complex for non-IT fluent chemists. –As a consequence, the efforts made for web services will be useful for a very limited audience. –Need to reach out normal chemists to help them leverage on the wealth of databases and analytical tools to advance their research.

6. Workflow automation Proposed solution: –Provide researchers with a high level query language (serialized through a GUI) that helps users formulate queries –Workflow automation will translate researcher query into executable workflow(s) –Provide users with different levels for workflow composition to account for different levels of user expertise

7. Workflow automation Example of existing solutions: Biomediator project (http://www.biomediator.org/publications/)http://www.biomediator.org/publications/

8. Workflow automation Example of existing solutions: SIBIOS project (http://sibios.engr.iupui.edu/) –Workflow automation component under construction –Solution using enhanced graph planner algorithm to translate user query into a workflow –Current status: the user needs to specify: the input and output of the workflow Potential intermediate services and their ordering

9. Workflow automation Example: –User inputs Swissprot entry (input) and needs to find associated nucleic acid definitions and organism names (output) –He also wants to query PDB service before GenBank service.

10. Workflow automation Future work: –Allow users to enter semantic queries using biological/bioinformatics concepts. –Generate more than one workflow as a solution for user query