Data reveals mechanisms in our bodies that can help us fight viral pathogenesis.

New apps help researchers with statistical analyses of data.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

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

Led by PNNL, the new Cathode-Electrolyte Interphase Consortium has been launched, involving 10 national laboratories and 10 universities.

A PNNL-developed computational framework accurately predicts the thermomechanical history and microstructure evolution of materials designed using solid phase processing, allowing scientists to custom design metals with desired properties.

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.

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

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

The Co-Optimization of Fuels & Engines initiative recently outlined six years of research in a findings and impact report.