The National Science Foundation awarded a $491,408 Project Grant to The Johns Hopkins University for research titled "CAREER: STATISTICAL APPROACHES AND COMPUTATIONAL TOOLS FOR ANALYZING SPATIALLY-RESOLVED SINGLE-CELL TRANSCRIPTOMICS DATA." The grant was awarded on July 15, 2021 under the Biological Sciences program (CFDA 47.074) to promote progress in the biological sciences and strengthen understanding of major problems facing the nation. The research aims to develop statistical...
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...
The Johns Hopkins University was awarded a $1.3 million Project Grant from the National Science Foundation Office of Advanced Cyberinfrastructure under the federal Computer and Information Science and Engineering grant program (CFDA 47.070) to develop the DATA CI PILOT: VARIMAT STREAMING POLYSTORE INTEGRATION OF VARIED EXPERIMENTAL MATERIALS DATA project from October 1, 2021 to September 30, 2023. Under the award, Johns Hopkins will advance data science and instrument streaming goals through...
This $276,308 Project Grant awarded by the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) supports the University of Oklahoma's research to develop novel computational and statistical methods for analyzing spatially-resolved single-cell genomics data. The project aims to: a) identify spatial gene expression patterns using a new two-dimensional statistical testing algorithm, b) gain data-driven insights into tissue changes and interactions in development and...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $118,760 to The Johns Hopkins University will support research to advance the state-of-the-art in optimization theory and algorithms for modern data science challenges. The project aims to develop novel computational and statistical analysis tools to understand the performance of off-the-shelf optimization heuristics, and leverage problem structure to design...
The National Science Foundation (NSF) awarded a $500,000 Project Grant to The Johns Hopkins University on August 15, 2023 under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant will fund the establishment of a 30 petabyte (PB) campus-wide research data storage facility at Johns Hopkins. This high-performance storage system will support a wide range of scientific research projects at the university, including large numerical simulations and microscopy data....
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award, totaling $299,996.00, supports the development of software to enable advanced analysis of linked datasets. The project aims to address challenges in post-linkage data analysis, a critical need for federal statistical agencies, researchers, and practitioners in health services. The software will provide robust, user-friendly capabilities for validation,...
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...
The National Science Foundation (NSF) awarded a $162,510 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Oklahoma to develop algorithms for scalable inference and phylodynamic analysis of tumor haplotypes using low-coverage single-cell sequencing data. The goal is to create a phylodynamic framework to jointly infer cancer phylogenetic trees and evolutionary parameters from single-cell DNA sequencing data. This will enable cancer...
The National Science Foundation (NSF) Office of Advanced Cyberinfrastructure awarded a $792,866 Project Grant to The Johns Hopkins University under the CFDA Program 47.070 - Computer and Information Science and Engineering. The grant supports the "Open SciServer" project, which aims to transition the existing SciServer data-driven science platform to an open-source, sustainable model. Key activities include migrating the codebase to open-source, enhancing administrative functions,...