Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.

SAGE is a high-efficiency genome integration strategy for bacteria that makes the stable introduction of new traits simple for newly discovered microbes.

Variations in burn severity are a key control on the chemical constituents of dissolved organic matter delivered to streams within a single burn perimeter.

First-of-its-kind genomic catalog lends insight into previously unknown processes at the river’s edge.

A multi-omics analysis provides the framework for gaining insights into the structure and function of microbial communities across multiple habitats on a planetary scale

Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.

Silicone wristbands could be more convenient option for collecting exposure data.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Hypergraphs can more faithfully identify important genes in complex immune responses.

The web-based tool, called PLATIPUS, is publicly available and interacts with publications available in the CovidScholar database.

New quantum chemistry pipeline can help predict the effects of bioengineering.

High-throughput biochemical assays targeting a vital viral protein identified one molecule out of more than 13,000 with promising antiviral activity against SARS-CoV-2.