SDIWG: NCBC DBP Interactions and Impact
This is the OLD page for the NIH Roadmap National Centers for Biomedical Computing (NCBC) Working Group titled: Driving Biological Projects Interactions and Impact Workgroup. The new page is http://www.ncbcs.org/dbp_interactions.html
An increasing number of biologists and biomedical researchers are beginning to rely on genome-wide knowledge about molecular and cellular interactions to dissect specific biological mechanisms and processes. For instance, coupling Quantitative Trait Loci (QTL) and genetic pathway data has been shown to help in the identification of low-penetrance susceptibility genes. Similarly, the study of differential gene expression analysis in normal vs. diseased tissue can benefit from the knowledge of the underlying genetic interaction networks, for instance to filter out downstream effects related to the dysregulation of a specific pathway. The ability to integrate, model and analyze such heterogeneous data in a controlled and reproducible way has emerged as a major challenge for biomedical research. Several NCBCs and their partners are actively working to enable and accelerate this process.
As a result, we believe that an important role of the National Centers for Biomedical Computing (NCBCs) will be providing the research community with tools, data, and methodologies for the analysis of cellular networks and for their use in the dissection of complex traits and biological processes for application to current and future Driving Biological Projects (DBPs).
The goal of this new workgroup, thus, is to help determine the specific research community needs for such resources as well as which NCBCs will provide or require specific tools and data integration capabilities in this area. This is especially important given the variety of existing and future Driving Biological Projects and collaborative R01 (PAR-05-063) and R21 (PAR-06-223) initiatives that may benefit from such activities. We recognize that a) such a “systems biology, modeling and analysis” approach may not be central to the mission of all the NCBCs; and b) that a large community of non-NCBC researchers (both producing and using such resources) exists. With respect to (a), we recognize that additional work is required related to this workgroup’s activities. With respect to (b), we must make sure that we coordinate our activities with other independent centers, projects and groups to help provide and link some of the key non-NCBC based resources available to the extended NCBC community. We acknowledge that these are very significant challenges (to be discussed). Resources fall broadly into at least three categories:
- Network reverse-engineering tools
- Optimization based (Bayesian Networks, etc.)
- Regression Methods
- Integrative Genomics
- Statistical and Information Theoretic
- Experimental data and measurements:
- Protein-protein: Interactomes
- Protein-DNA: DNA binding site data
- Protein-DNA: ChIP-chip data
- Proteomic and Metabolic measurements
- Data from Biomedical and Biological Literature and Databases
- Data from imaging studies
- Network Analysis Tools:
- Evidence Integration
- Visualization (passive and interactive)
- Differential expression
- Modeling and Simulation
Furthermore, while cellular networks are fully integrated within the cell, it is often useful to think of different layers of interactions, mostly because of the differences in experimental data acquisition methodologies that apply to each layer. These include:
- Transcriptional Networks
- Signal Transduction Networks
- Protein-protein interaction in stable complexes
- Metabolic Networks
Thus, many of the data and computational resources above may play differently in the context of each interaction layer. This further contributes to the complexity of the application of these tools and capabilities, but also opens the door for considering these problems as an important case of multi-scalar modeling and analysis. A major goal of this workgroup is to synthesize the various efforts ongoing within the NCBC community, including strategies to link these efforts into the work being done in the broader community. In addition, we are especially interested in understanding the needs and approaches identified and being currently implemented in the various DBPs in the full complement of the NCBCs. We are specifically interested in exploring DBPs that span many NCBCs (e.g. Diabetes, Schizophrenia) or pathways/approaches that are shared by several DBPs.
As discussed, while some of the NCBCs are actively contributing some of these resources, the territory is simply too vast to be fully covered by the NCBCs alone. As a result, we are establishing close collaborations with individual investigators and with other centers of excellence. The goal is to establish a set of resources that would be easily accessible to existing and future DBPs, to investigators writing collaborative proposals, and to the broader NIH research community. This activity is meant to leverage and interact with the “Software Yellow Pages and Resourcome” and the “Scientific Ontology” workgroup products.
A recent activity, among these harmonization efforts, is the organization of the DREAM workshop and database. This is intended to create a quantitative platform to assess the quality of predictions made by reverse engineering algorithms. This initiative has been broadly supported by the international reverse engineering community. The following document summarizes the planning activities and conclusions of the DREAM planning meeting, which was held on March 9th and 10th 2006 at the New York Academy of Sciences ( DREAM Kickoff Meeting Summary). The first DREAM meeting will be held on Sept. 7 and 8 in the Wave Hill Convention Center, New York NY. See Workshop Announcement for details.
We look forward to seeing everyone in Bethesda and getting started on this new direction for the NCBCs.
Highlights from Systems Biology TCONs
Report from the All Hands Meeting, Working Group