The National Science Foundation awarded $665,786 under the Biological Sciences federal grant program (CFDA 47.074) to the University of North Carolina at Chapel Hill from March 2023 through February 2027. The project aims to advance understanding of long noncoding RNAs (lncRNAs) and their potential for epigenetic regulation through rational design and engineering of synthetic lncRNAs. Researchers will define the minimal features required for large-scale silencing mediated by lncRNAs, building...
This Project Grant from the National Science Foundation Division of Emerging Frontiers, under the Biological Sciences federal grant program (CFDA 47.074), provides $932,563 to support research into the discovery of novel functional RNA classes through computational integration of massively parallel RNA-binding protein binding and structure data. The President and Fellows of Harvard College will utilize highly multiplexed approaches to generate transcriptome-wide measurements of hundreds of...
This $2.11 million project grant from the National Science Foundation's Division of Emerging Frontiers, under the Biological Sciences federal grant program (CFDA 47.074), will fund research at Emory University and the University of Tennessee from March 2023 through February 2027 to rationally design long noncoding RNAs (lncRNAs) for epigenetic signal amplification. The researchers will define the minimal features required for large-scale silencing mediated by lncRNAs, building on the...
This $469,407 project grant from the National Science Foundation Division of Molecular and Cellular Biosciences, under the Biological Sciences federal grant program (CFDA 47.074), will fund research to discover novel functional RNA classes through computational integration of massively parallel RNA-binding protein binding and structure data. The awardee, Georgia Tech Research Corporation, will conduct this research from March 2023 through February 2028. Specifically, the organization will...
This $1,042,995 National Science Foundation project grant, awarded on March 15, 2023 under the Biological Sciences (47.074) program, funds research at Oregon State University and Mount Holyoke College to discover novel functional RNA classes through computational integration of massively parallel RNA-binding protein binding and structure data. The grantees will develop new experimental and computational methods to systematically identify unknown non-coding RNA classes by combining known and...
This $340,312 federal Project Grant award from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) aims to advance computational methods for large-scale transcriptome profiling. The award supports the development of innovative algorithms to improve the accuracy and scalability of computational methods for assembling and analyzing data from high-throughput RNA sequencing experiments. This work promises to enable more precise measurements of gene expression and...
This $1,555,035 Project Grant from the National Science Foundation Division of Molecular and Cellular Biosciences will fund research into the discovery of novel functional RNA classes through computational integration of massively-parallel RBP binding and structure data. The award was made under the Biological Sciences federal grant program (CFDA 47.074) to support basic biological research strengthening the nation's scientific enterprise. The California Institute of Technology will use the...
The National Science Foundation awarded a $673,715 project grant to The University of North Carolina at Charlotte under the Biological Sciences federal grant program (CFDA 47.074) for the period of May 1, 2021 through April 30, 2024. The grant funds the "IIBR INFORMATICS: ACCURATE ASSESSMENT OF PROTEIN-DNA COMPLEX MODELS AND APPLICATIONS" project. This project aims to advance scientific knowledge and understanding of major problems in the biological sciences, as outlined in the program...
This $741,002 federal Project Grant award from the National Science Foundation's Biological Sciences program supports the development of a novel machine learning framework for analyzing large-scale, multi-modal single-cell biological data. The project aims to construct advanced computational tools and user-friendly software to enable more effective extraction of insights and knowledge from complex single-cell datasets spanning genomics, transcriptomics, epigenomics, and proteomics. The...
This National Science Foundation (NSF) Project Grant award under the Biological Sciences program (CFDA 47.074) provides $522,131.00 to New York University (NYU) from August 1, 2023 to July 31, 2026. The funded research aims to understand the relationship between RNA sequence features and splicing outcomes, as well as the role that nuclear speckles play in RNA splicing decisions. The project will leverage high-throughput assays and interpretable machine learning to identify sequence-encoded...
This Project Grant from the National Science Foundation Division of Biological Infrastructure totaling $662,630 will fund the development of a computational approach to identify non-linear sequence similarity between long noncoding RNAs (lncRNAs). The University of North Carolina at Chapel Hill will utilize the award under the Biological Sciences federal grant program (CFDA 47.074) to create HMMseekr, a Python-based software package that applies hidden Markov models to identify regional and whole-transcript similarities in k-mer content between lncRNAs. This will address limitations in current tools and provide biologists with improved capabilities to discern relationships between sequence and function in lncRNAs. Validation will involve applying HMMseekr to detect known protein-binding domains and characterize additional lncRNAs from mammalian transcriptomes. Findings and a vetted version of the software will be published openly along with recommendations for default parameters and usage guidance. The award also supports high-quality research experiences for undergraduate students from underrepresented backgrounds.