CICC June meeting

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.edu8080/biofa
  cets/)
• 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/)
  

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