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The rhizosphere represents a dynamic and complex interface between plant hosts and the microbial community found in the surrounding soil. While it is recognized that manipulating the rhizosphere has the potential to improve plant fitness and health, engineering the rhizosphere microbiome through...

Agriculture is the largest source of greenhouse gases (GHG) production. Conversion of nitrogen fertilizers into more reduced forms by microbes through a process known as biological nitrification drives GHG production, enhances proliferation of toxic algal blooms, and increases cost of crop...

Metabolite exchange between plant roots and their associated rhizosphere microbiomes underpins plant growth promotion by microbes. Sorghum bicolor is a cereal crop that feeds animals and humans and is used for bioethanol production. Its root tips exude large amounts of a lipophilic benzoquinone...

A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery...

The Sequel II System Sequencer is a high-throughput DNA sequencer machine developed and manufactured by PacBio , and is designed for high throughput, production-scale sequencing laboratories. Originally released in 2015, the Sequel system provides Single Molecule, Real-Time (SMRT) sequencing core...

The Human Islet Research Network (HIRN) is a large consortia with many research projects focused on understanding how beta cells are lost in type 1 diabetics (T1D) with a goal of finding how to protect against or replace the loss of functional beta cells. The consortia has multiple branches of...

  1. Datasets

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The database contains observational analyses and model results that are used in publications, reports and/or manuscripts in review, related to climate and environmental changes of the Earth system, especially in high-latitude regions. This is for the HiLAT project, which is a SFA supported by DOE...
The database contains observational analyses and model results that are used in publications, reports and/or manuscripts in review, related to climate and environmental changes of the Earth system, especially in high-latitude regions. This is for the HiLAT project, which is a SFA supported by DOE...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...
Both the hourly and daily data are provided in the product. The hourly data are grouped by day in distinct NetCDF files, which are named as “EPIC_SW_PAR_Hourly_yyyymmdd.nc” where “yyyy”, “mm”, and “dd” denote year, month, and day (UTC time). The daily data are grouped by month in distinct NetCDF...