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The funding information displayed below comes from the
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NSF Award Database.
The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Samuel Angiuoli is the likely recipient of the following grants.
Years |
Recipients |
Code |
Title / Keywords |
Matching score |
2010 — 2013 |
Wommack, K. Ravel, Jacques White, Owen [⬀] Angiuoli, Samuel Mahurkar, Anup |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Mri-R2: Acquisition of Data Intensive Academic Grid (Diag) @ University of Maryland At Baltimore
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Support from the NSF MRI-R2 program allowed the University of Maryland at Baltimore to build the Data Intensive Academic Grid (DIAG) that includes 100 nodes for high-throughput computational analysis and 5 nodes for high-performance computational analysis. This resource will optimize data sets generated by mining the data from public data repositories like Community Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis (CAMERA) and the National Center for Biotechnology Information and will leverage technologies developed for existing grid resources such as the TeraGrid, and Open Science Grid. The bioinformatics community will access the DIAG using Ergatis, a web based pipeline creation and management tool, bioinformatics oriented Virtual Machines, as well as interactive and programmatic access using technologies such as Nimbus and the Virtual Data Toolkit from the Open Science Grid. The software produced at the DIAG site will be easily utilized by projects such as the Globus Workspaces Project, Open Science Grid and other projects involving large multi-institutional collaborations, as well as providing spillover capacity for two other science grids, located in Illinois and California. The DIAG development will enable training of the next generation of biologists, by bringing a powerful new analysis system to undergraduate, graduate, and post-graduate students in 15 different classroom settings, and the allocation of system time to universities with predominantly under-represented minorities, greatly enhancing the available computation and computing infrastructure for these groups.
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0.966 |