Service Oriented Bioscience Cluster at OSC

1
Service Oriented Bioscience Cluster at OSC

• Umit V. Catalyurek
• Associate Professor
• Dept. of Biomedical Informatics
• Dept. of Electrical Computer Engineering
• The Ohio State University

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Origins of caBIG

• Goal Enable investigators and research teams
  nationwide to combine and leverage their findings
  and expertise in order to meet NCI 2015 Goal.
• Strategy Create scalable, actively managed
  organization that will connect members of the
  NCI-supported cancer enterprise by building a
  biomedical informatics network

Relieve suffering and death due to cancer by the
year 2015
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Driving needscancer Biomedical Informatics Grid

• A multitude of legacy information systems, most
  of which cannot be readily shared between
  institutions
• An absence of tools to connect different
  databases
• An absence of common data formats
• A huge and growing volume of data must be
  collected, analyzed, and made accessible
• Few common vocabularies, making it difficult, if
  not impossible, to interlink diverse research and
  clinical results
• Difficulty in identifying and accessing available
  resources
• An absence of information infrastructure to share
  data within an institution, or among different
  institutions

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What is caBIG?

• Common, widely distributed infrastructure that
  permits the cancer research community to focus on
  innovation
• Shared, harmonized set of terminology, data
  elements, and data models that facilitate
  information exchange
• Collection of interoperable applications
  developed to common standards
• Cancer research data available for mining and
  integration

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What is caGrid?

• A grid based software infrastructure consisting
  of services, toolkits, APIs, and applications
• A production grid deployment of the core services
  provided by that infrastructure
• A community of developers leveraging that grid
  and infrastructure to provide applications and
  services to the cancer research community

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What is caGrid?

• Development project of Architecture Workspace
• The Grid infrastructure for caBIG (the G in
  caBIG)
• Driven from use cases and needs of cancer
  research community
• Service Oriented Architecture
• Based on federation
• Model Driven
• Object-Oriented, Semantically-Annotated Data
  Virtualization

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What is caGrid? cont

• Builds on existing Grid technologies
• Provides additional enterprise Grid components
• Grid Service Graphical Development Toolkit
• Metadata Infrastructure
• Advertisement and Discovery
• Semantic Services
• Data Service Infrastructure
• Analytical Service Infrastructure
• Identifiers
• Workflow
• Security Infrastructure
• Client tooling

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caGrid Community Involvement

• caGrid itself provides no real data or
  analysis to caBIG its the enabling
  infrastructure which allows the community to do
  so
• Community members add value to the grid as
  applications, services, and processes (for
  example shared workflows)
• caGrid provides the necessary core services,
  APIs, and tooling
• The real value of the grid comes from bringing
  this information to the end user
• Community members develop end user applications
  which consume of the resources provided by the
  grid

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caGrid _at_ OSC

• Goals
• Create an expandable caGrid Installation at OSC
• Deploy Pilot Applications to demonstrate
• Service Oriented Access to HPC resources
• Dorian, GTS and Index services are deployed
• cagrid-dorian01.osc.edu
• cagrid-gts01.osc.edu
• cagrid-index01.osc.edu
• SyncGTS along with Dorian and Index for
  performance
• caGrid 1.2 was released this week, and we
  deployed it!

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Pilot Application TMA

• Image Mining for Performing Comparative Analysis
  of Expression Patterns in Tissue Microarrays
• Project funded by NIH R01 (PI David Foran,
  Co-PI Joel Saltz)
• Development of innovative analysis methods for
  analysis of tissue microarrays
• Computation of features, annotations of image
  data based on features
• Development of software support
• to manage and share tissue microarray data and
  analysis results
• to process large volumes of tissue microarray
  data on high performance systems
• Development of ability to share data and
  analytical resources using caGrid
• Supports Help Defeat Cancer project which 100,000
  imaged histology specimens originating from
  breast, head neck, colorectal cancers.

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TMA Analytical Service Implementation

• TMA Application is a pipelined workflow
• Several processing steps that need to be applied
  in sequence to the images
• Build a prototype workflow orchestration system
• Wraps a program execution
• Stages the the data in
• Invoke the executable
• Retrieve the output files
• Uses caGrids bulk data transfer to move files
  from host to host
• Interacts with a scheduler to allocate resources
  for the execution
• Executable can be a parallel/distributed
  application
• TMA user interface
• Specify the workflow
• List with executables and parameters
• Invoke the service for the first stage

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What is next?

• Next Pilot Application Prof. Dan Janies
  Supramap
• http//supramap.osu.edu
• Builds a phylogenetic tree and projects onto the
  map of the planet
• Computationally expensive
• Next Pilot Application(s) Your Application!?
• More Info http//bmi.osu.edu and
  http//www.cagrid.org
• Contact Umit V. Catalyurek email
  catalyurek.1_at_osu.edu