This $794,457 federal Project Grant award from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) will support the development of new genetic analysis tools. The goal is to incorporate molecular and cellular biology knowledge, such as gene expression patterns and regulatory networks, directly into statistical models used to map genes, predict traits, and simulate changes in the genotype-to-phenotype relationships. The research will be conducted using simulated...
Colorado State University will provide research, education, and outreach services under a $622,699 Project Grant from the National Science Foundation Division of Integrative Organismal Systems. The grant falls under the NSF Biological Sciences program (CFDA 47.074) and aims to facilitate the prediction and validation of plant enzyme functions through three key activities. First, CSU will deposit published plant enzyme activities into public databases to support computational function...
This Project Grant award from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) supports the development of new computational tools for analyzing single-cell genomic data across diverse plant species. The $1,180,752 award to Virginia Polytechnic Institute & State University aims to address key challenges in plant single-cell transcriptomics, including determining known and novel cell types, enabling cross-species comparisons, and overcoming the lack of curated...
This $341,473 Project Grant award, funded by the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074), supports research to develop new methods for measuring plant traits using leaf spectroscopy on herbarium specimens. The primary objective is to enable large-scale assessments of how plant functional traits and their combinations have evolved across different biomes, such as rainforests, savannas, and deserts. The research will generate new phylogenetic data and...
This National Science Foundation (NSF) Biological Sciences (CFDA 47.074) Project Grant award, valued at $726,093 and spanning from April 1, 2025 to March 31, 2028, is funding research by the University of Washington to develop programmable and tunable regulatory elements for predictive gene expression in plants. The goals are to: Create a large repertoire of synthetic regulatory elements using massively parallel reporter assays, machine learning, and in silico evolution. Precisely control gene...
This $1,999,998 National Science Foundation Project Grant, funded under the Biological Sciences program (CFDA 47.074), supports research at the University of Washington to advance plant synthetic biology through deciphering the grammar of crop gene regulatory elements. The three-year award beginning March 1, 2023 will apply massively parallel reporter assays and machine learning to characterize tens of thousands of genetic regulatory elements in maize and tomato, including enhancers,...
This $998,790 project grant from the National Science Foundation's Biological Sciences program (CFDA 47.074) will support enhancing global plant transformation capacity through research, training, and partnerships led by Boyce Thompson Institute For Plant Research Inc. Over a three-year period, the grantee will establish a global research coordination network to collectively address challenges to plant genetic engineering and gene editing efficiency. The network aims to facilitate collaboration,...
This $220,848 two-year Project Grant from the National Science Foundation's Division of Molecular and Cellular Biosciences will fund the development of new approaches for spatial transcriptome analysis in plants under the Biological Sciences program (CFDA 47.074). The awardee, Virginia Polytechnic Institute and State University, will leverage existing fluorescent reporter gene lines to perform single-cell RNA sequencing and fluorescent imaging of the meristematic region of plant roots. Machine...
This $331,858 National Science Foundation project grant supports research at Wake Forest University to develop new machine learning techniques for analyzing plant morphology data. The goal is to identify evolutionary processes underlying rapid innovation in flowering plants during the Cretaceous period. Key products include a large dataset of morphological traits for fossil and living plant species generated using novel machine learning methods. The project will also develop new statistical...
This Project Grant award from the National Science Foundation's Biological Sciences program (CFDA 47.074) provides $300,000 in funding to Western University of Health Sciences to conduct collaborative research on the variability and regulation of the plant polyadenylation complex. The research aims to better understand how this complex mediates gene expression and plant responses to environmental and developmental cues, with the goal of improving our knowledge of crop plant growth,...