DOE Performance Metrics

Every year BER’s Biological Systems Science Division (BSSD) reports on various aspects of its basic science mission as part of DOE’s performance management process. Listed below are several reports offered by year from various BSSD-funded projects highlighting recent basic research results relevant towards achieving BER’s long-term performance goals. Individual projects charged with completing these tasks produce quarterly reports on the requested topic that show progress toward the targeted goal for that year and ultimately toward the Overall Goal for BSSD.

Overall Goal: BER Predictive Understanding
Advance an iterative systems biology approach to the understanding and manipulation of plant and microbial genomes as a basis for biofuels development and predictive knowledge of carbon and nutrient cycling in the environment.

Year	Project and Goal	Quarterly Reports	Project Website
2024	The National Microbiome Data Collaborative: Approaches to assemble a centralized microbiome data collection to understand the functioning of microbiomes relevant to BER’s bioenergy and environmental research goals. Q1: Describe the overall background, strategy, and challenges to developing an online, open access microbiome data collection for the research community. Q2: Describe the mechanisms developed to engage the broader community to assist in the development of a community-based resource for microbiome research. Q3: Report on the strategy to engage with other entities for access to data resources and/or modeling efforts for microbiome research. Q4: Provide an update on the latest capabilities developed within the NMDC for providing a unique data resource to the larger microbiome research community.	Q1 Report Q2 Report	Visit Project Website
2023	PNNL Secure Biosystems Design SFA: Develop genomic approaches to securely design organisms with targeted beneficial functions for bioenergy and bioeconomy applications. Q1: Describe overall approaches to securely designing new functions into organisms for bioenergy and bioeconomy applications. Q2: Report on progress towards designing new secure functions into specific microbial isolates in the laboratory. Q3: Provide a summary of methods used to characterize and test modified microorganisms for secure use. Q4: Report on capabilities that could accelerate the design and testing of microbial isolates with new beneficial functions.	Q1 Report Q2 Report Q3 Report Q4 Report 2023 Summary
2022	LBNL ENIGMA SFA: Develop new technologies for assessing microbial ecological processes in environmental samples.	Q1 Report Q2 Report Q3 Report Q4 Report 2022 Summary	View Project Website
2021	LLNL Microbes Persist Soil Microbiome SFA: Develop new omics-based techniques to understand microbiome function in environmental samples.	Q1 Report Q2 Report Q3 Report Q4 Report 2021 Summary	View Project Website
2020	ORNL Center for Bioenergy Innovation (CBI): Report on genomic science-based advances and testing of new plant feedstocks for bioenergy purposes.	Q1 Report Q2 Report Q3 Report Q4 Report 2020 Summary	View Project Website
2019	LANL Terrestrial Microbial Carbon Cycling SFA: Develop metagenomics approaches to assess the functioning of microbial communities in the environment. (See DOE Performance Metrics tab.)	Q1 Report Q2 Report Q3 Report Q4 Report 2019 Summary
2018	ORNL Plant-Microbe Interfaces SFA: Using genomics-based techniques, develop an approach to explore the functioning of plant-microbe interactions.	Q1 Report Q2 Report Q3 Report Q4 Report 2018 Summary	View Project Website
2017	DOE Systems Biology Knowledgebase (KBase): Develop improved open access platforms for computational analysis of large genomic datasets.	Q1 Report Q2 Report Q3 Report Q4 Report 2017 Summary	View Project Website
2016	Joint BioEnergy Institute (JBEI): Develop an improved metabolic engineering method for modifying microorganisms for biofuel production from cellulosic sugars.	Q1 Report Q2 Report Q3 Report Q4 Report 2016 Report	View Project Website
2015	DOE Joint Genome Institute (JGI): Develop one new computationally enabled approach to analyze complex genomic datasets.	Q1 Report Q2 Report Q3 Report Q4 Report 2015 Summary	View Project Website