Project Grant 2125218
- This $248,508 National Science Foundation project grant supports the development of computational tools and a database for modeling protein-protein and protein-nucleic acid interactions involving intrinsically disordered regions. Funded under the Biological Sciences program (CFDA 47.074), key products include high-accuracy prediction of binding regions within disordered sequences using multi-task deep learning models; identification of partner molecules for these regions; and structure...
- This $999,999.00 Project Grant award from the Department of Defense under the Basic, Applied, and Advanced Research in Science and Engineering program (CFDA 12.630) supports research at Virginia Commonwealth University (VCU) to accelerate the design of de novo protein libraries for directed deposition of patterned semiconductor nanomaterials using machine learning techniques. The 4-year award, which began on April 1, 2025, aims to advance scientific research with potential long-term...
- The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $150,000 project grant to The University of Kentucky Research Foundation to develop deep-learning consistency models for simulating long-time scale protein dynamics. This 2-year project (8/1/2025 - 7/31/2027) aims to address the limitations of current molecular dynamics simulations in capturing the long-duration dynamics crucial for understanding protein folding and aggregation. By...
- This federal Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) in the amount of $100,000 will support collaborative research to develop deep learning-based "consistency models" that can simulate protein dynamics over long time scales. The goal is to overcome the limitations of current molecular dynamics simulation methods, which are constrained by the need for tiny time steps, in order to unlock new insights into protein behavior and...
- The National Science Foundation Division of Information and Intelligent Systems awarded Indiana University a $113,029 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports research that will integrate deep learning and high-throughput experimentation to engineer proteins for non-native enzyme catalysis. Researchers will develop artificial intelligence models to interpret experimental data and guide iterative protein design. Two classes...
- The University of Virginia (UVA) received a $600,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) to advance federated graph machine learning (FGML) techniques. The project aims to 1) address data heterogeneity challenges in FGML, 2) develop novel algorithms to tackle label deficiency issues, and 3) strengthen data privacy protection for node attributes and graph structures. The research will produce...
- The National Science Foundation Office of Advanced Cyberinfrastructure awarded Virginia Polytechnic Institute and State University a $499,999 Project Grant under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The five-year award will support research to advance data valuation techniques for machine learning applications. Specifically, the university will conduct four research tasks to enable data valuation to overcome challenges related to...
- This National Science Foundation project grant of $248,782 awarded on March 15, 2022 will fund the development of computational tools and a database for understanding intrinsically disordered protein-protein and protein-nucleic acid interactions through February 28, 2025. Funded under the Biological Sciences program (CFDA 47.074), Purdue University will create three interlocking computational methods at the 1D, 2D, and 3D levels to advance prediction and modeling of tertiary structures for...
- This Project Grant award from the National Science Foundation's (NSF) Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) provides $599,948 to George Mason University, doing business as Mason, to advance algorithmic research at the intersection of information integration and informatics using principled protein language models (PLMs) as computational vehicles. The key objectives of this 3-year project are to: (1) encode prior...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $200,000 provides funding to Virginia Polytechnic Institute & State University (Virginia Tech) from September 1, 2024 to August 31, 2027. The project aims to create a more automated and generic framework, along with effective tools, to distill fundamental knowledge of feature spaces and build AI-ready feature spaces using deep generative...
Virginia Commonwealth University was awarded a $500,000 Project Grant from the National Science Foundation Division of Information and Intelligent Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research to develop integrated prediction of intrinsic disorder and disorder functions using modular multi-label deep learning. The project aims to advance computational methods for characterizing intrinsically disordered protein regions and their functional associations, which will enhance understanding of protein structure and function. The university will deliver research outcomes and knowledge gained over the course of the award period ending September 2024.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $500.0k | 8/31/21 |