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Funding Opportunities

Climate Change and Health: Assessing and Modeling Population Vulnerability to Climate Change (R21)

• Application Due Date(s): September 28, 2010; May 24, 2011; May 24, 2012
• This FOA encourages research applications to examine the differential risk factors of populations that lead to or are associated with increased vulnerability to exposures, diseases and other adverse health outcomes related to climate change. Applications may involve either applied research studies that address specific hypotheses about risk factors or population characteristics associated with increased vulnerability, or research projects to develop general models or methods for identifying and characterizing population vulnerability to climate change.
• More Information

NIBIB Challenge Topics relevant to Modeling and Analysis

For a complete listing of NIBIB Challenge Topics, http://www.nibib.nih.gov/ChallengeGrants

Challenge Grant Guidelines, http://grants.nih.gov/grants/guide/rfa-files/RFA-OD-09-003.html

Application Due Date April 27, 2009

NIH Notice regarding Foreign Subcontracts, http://grants.nih.gov/grants/guide/notice-files/NOT-OD-09-061.html

06-EB-109 – Model-Driven Biomedical Technology Development Progress in the development of many biomedical technologies (e.g. neuroengineering technologies, drug and gene delivery systems, tissue engineering) could be greatly accelerated with the development of in silico modeling and simulation methods to drive hypothesis formation, experimental design, data collection, data analysis and synthesis, and re-formulation of the original hypothesis. In a systematic and robust manner, models should identify the gaps in knowledge and the limitations of the engineering design. Proposals that encourage the integration and translation of knowledge from in vitro to in vivo systems are being sought. Contact: Dr. Grace Peng, 301-451-4778, penggr@mail.nih.gov

06-EB-110 – Methods for Assessment of Imaging Technologies Proposals to develop mathematical, statistical or computation models that can be used by technology developers to assess or calibrate their medical imaging technologies are encouraged. Contact: Dr. Zohara Cohen, 301-451-4778, zcohen@mail.nih.gov

06-EB-111 – Validation of Image Analysis Methods Applications are sought that provide an infrastructure for the evaluation of image registration and segmentation algorithms. This infrastructure is expected to include a database of test images, a web-based interface with public access, consensus-driven evaluation metrics, and a system for storing and reporting measures associated with different algorithms. Contact: Dr. Zohara Cohen, 301-451-4778, zcohen@mail.nih.gov

06-EB-112 – Large-Scale Kinetics of Multiple Signaling Pathways Building upon successful efforts in detailed kinetic modeling of highly-complex chemical reactions (e.g., turbulent combustion), large-scale kinetic models of multiple and integrated molecular signaling pathways are sought. This will help determine under which conditions particular pathways may dominate or interfere, and begin to form a predictive framework as new kinetic data and signaling molecules are identified. Construction of these models will highlight important kinetic information gaps and pave the way toward ultimately being able to perform in silico simulations of inflammatory and immune response to new materials and engineered therapies. Contact: Dr. Albert Lee, 301-451-4781, alee@mail.nih.gov

10-EB-102 – User-Friendly Computing Infrastructures for Biomedical Researchers and Clinicians Openly available computing infrastructures that link to shared research and clinical databases as well as robust analysis and visualization tools need to be available to users who do not have prior computing expertise. Rather than spending time on understanding how to use the tools, these infrastructures will allow researcher to focus on synthesizing knowledge. The infrastructures should be seamlessly integrated in the research and clinical environment and provide optimal usability for all researchers. Projects should focus on linking existing databases, models, algorithms, visualization tools and developing the user-friendly interface environment. Contact: Dr. Zohara Cohen, 301-451-4778, zcohen@mail.nih.gov

15-EB-101 – Towards the Virtual Patient Disease prediction, now more than ever, can benefit from the wealth of knowledge of gained from decades of basic biomedical research. Computational models provide the critical tools to integrate this knowledge with a systems approach to diseases. Disease prediction will require the integration of existing physiome models and multiscale models from multiple biological systems. In addition, standardized shared datasets will need to be created to achieve model validation. Contact: Dr. Grace Peng, 301-451-4778, penggr@mail.nih.gov