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MAGNet Center: Andrea Califano NCIBI: Brian Athey Simbios: Russ Altman Creating a DBP Community to Enhance the NCBC Biomedical Impact NCBC Work Group Report,

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Presentation on theme: "MAGNet Center: Andrea Califano NCIBI: Brian Athey Simbios: Russ Altman Creating a DBP Community to Enhance the NCBC Biomedical Impact NCBC Work Group Report,"— Presentation transcript:

1 MAGNet Center: Andrea Califano NCIBI: Brian Athey Simbios: Russ Altman Creating a DBP Community to Enhance the NCBC Biomedical Impact NCBC Work Group Report, 18 July 2006

2 Workgroup Goals Problem: The NCBCs have no workgroup to help build the DBP community Goal 1: To determine the Mission and Goals for the Applications of Systems Biology, Modeling and Analysis Working Group Goal 2: To determine how this group would interact with the 2 other NCBC Working Groups to define key sets of:  Data  Tools  Methodologies  Ontologies  DBPs Goal 3: Identify NCBC DBPs that are highly motivated to participate in the Working Group Goal 4: How to link to external communities (e.g., DREAM-like activities)? Additionally: Discuss as a focused example “Molecular Interaction Maps” in the context of the DBPs

3 DBP Success Depends on the Availability of an Integrated Resourceome (Not a priority for Core I/Core II Projects) Integrated Computational Biology Platform Support for gene expression data, physics- based simulations, image analysis, sequences, pathways, structure, etc. (40+ visualization and analysis modules). Access to local and remote data sources and analytical services. Support for workflow scripting. Integration with grid infrastructures. Development framework Open source development. Modular/extensible architecture, supporting pluggable components with configurable user interface. Easy integration of 3 rd party components. … The integration process must be driven by the DPB requirements rather than by Core I/II activities.

4 We Must Work With the “Yellow Pages” WG to Assemble an Indexable List of Most Useful Tools and Platforms Many Toolkit and platforms  Internal SimTk Genopia VTK/ITK Brainsuite geWorkbench GenePattern MiMI SAGA miBLAST MarkerInfoFinder  External GenePattern Systems Biology Workbench myGRID Cytoscape and ISB tools How do we make these tools interoperable? This must be DBP-driven because other cores (I/II) do not necessarily depend on tool interoperability.

5 GenePattern/geWorkbench Interoperability: An Opportunity and a Starting Point KNN WV SVM SOM GSEA ARACNE SPLASH PCA GenePattern Module Repository Wrap geWorkbench modules as GenePattern tasks Execute GenePattern modules from within geWorkbench

6 Interactions with the Scientific Ontology Working public DSDataSet publish(...) { DSDataSet dataSet; // do some work that assigns a value to dataSet. return dataSet; public void receive(DSDataSet dataSet, Object source) { // Consume the argument dataSet, as appropriate } Provide re-usable models of common bioinformatics concepts:  Data: sequence, expression, genotype, structure, proteomics  Complex data structures: patterns, clusters, HMMs, PSSMs, alignments  Algorithms: Clustering, matching, discovery, normalization, filtering Provide a foundation for the development of interoperable geWorkbench components Endorsed by multiple communities (caBIG, AMDeC, NCBCs) Component A Component B

7 Identifying Specific Tools There are tools, databases, and methods that have universal value across different DBPs.  What are they?  Which NCBC or external community is producing them  What can we do to standardize their use across the community. An Example:  Molecular Interaction Maps

8 A Relevant Example That Was Discussed Molecular Interaction Maps are becoming the equivalent of an anatomy atlas to map specific measurements in a functional context; e.g. QTLs, expression profiles, etc. Discussion Goal: To determine how relevant these maps are to the DBPs of the various NCBCs Limitations: Many Interactomes are limited because they are (1) too generic (e.g. missing cellular and molecular context), (2) poorly annotated (e.g. linked only to the specific data used to produce them), (3) limited to pairwise interactions, (4) lacking quality control/validation, and (5) not associated to the investigation of specific biological/biomedical problems.

9 Example: From Molecular Interaction Maps to Molecular Interaction Knowledge Bases What does it take to turn a ridiculome into a relevantome?  Quality control metrics (recall/precision)  Context specificity Cellular: Is the interaction specific to a cellular phenotype Molecular: Is the interaction dependent on the availability of other molecular species  Links to data (and literature)  Links to analysis of biomedical problems  Focus on specific features (e.g. mechanisms)

10 A Potential Template for NCBC Knowledge Bases: MAGNet Human B Lymphocytes Dataset Integrative Framework  Bayesian Evidence integration of pairwise interactions Protein-Protein, Protein-DNA Prior Knowledge Incorporation Context Specific  ARACNE, GeneWays, REDUCE B-Cell data or B-cell specific criteria  Linked to one of the largest B-Cell expression profiles microarray dataset, ChIP- Chip assays (MYC/BCL6), miRNA profiles, and Literature Captures Multi-variate dependencies  Three-way interactions via MINDY and MATRIXReduce Post-translational modulation of transcriptional regulation  Combinatorial transcriptional regulation  Signal transduction control of Transcriptional Regulation I.e. the Transferome meets the Transcriptome Links to literature (via GeneWays, NCIBI, I2B2, GATE, etc.) Other examples? Oncomine (NCIBI), GenePattern ALL/AML, Others? Example

11 Some Key Observations from Attendees: Systems Biology name is too narrow. Think of Alternatives:  “Working group to Biomedical Impacts of Computational Biology at NCBCs” or  NCBC Biomedical Impact Workgroup Is the intramural program a better place to create atlases and knowledge bases, since it’s not RO1 funding? They could implement contract mechanisms with extramural researchers to leverage outside expertise Keep in mind that we need to understand what will you deliver at the end of 4 years, positioning each NCBC for renewal. Which communities are using the tools? Are they better off? Individual centers can work to create a specific resourceome that can be linked and accessible to others Many working group members had a strong interest in “multi- scale” modeling and biological context

12 Outcomes: Create a DBP community within the NCBCs:  ACTION: Make an interactome map of the existing DBPs with potential synergies to be published in Symbios magazine Use this forum to inform target biological communities (not just NCBCs). E.g. DREAM meeting. Organize a coordinated effort to evaluate the tools and technologies and make them interoperable  ACTION: Coordinate the DBP requirements to drive the integration of specific tools and data resources Integrate data and annotation in knowledge bases and models for related DBPs. Identify other common tools, data, and methods Drop the Systems Biology name: Use something like:  “NCBC Biomedical Impact Workgroup” Commit to a regular T-con and virtual (Wiki) participation Consider a yearly retreat of NCBC DBPs possibliy in collaboration with other NIH roadmap activities (e.g. ICBPs)

13 NCBC DBP Interactome I: Useful Starting Point Peter Woolf, NCIBI

14 Distribution Model: How Can the 7 NCBCs Effectively Interoperate? Informatics for Integrating Biology and the Bedside (i2b2) Isaac Kohane, PI Center for Computational Biology (CCB) Arthur Toga, PI Multiscale Analysis of Genomic and Cellular Networks (MAGNet) Andrea Califano, PI National Alliance for Medical Imaging Computing (NA-MIC) Ron Kikinis, PI The National Center For Biomedical Ontology (NCBO) Mark Musen, PI Physics-Based Simulation of Biological Structures (SIMBIOS) Russ Altman, PI National Center for Integrative Biomedical Informatics (NCIBI) Brian D. Athey, PI


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