KBase: The Department of Energy Systems Biology Knowledgebase

KBase is an open platform for comparative functional genomics and systems biology for microbes, plants and their communities, and for sharing results and methods with other scientists.

News

New KBase Help Board

KBase is committed to helping all our users to utilize our tools and datasets for their computational biology research. To make our support process more effective, we are rolling out a new, more interactive way for users (and prospective users) to report bugs, ask questions, or suggest new features, using an issue tracking system called […]

System update on Tuesday, December 6 will cause downtime

The latest release of KBase will be rolled out on Tuesday, December 6. This will make KBase functionality unavailable starting at 8:00am PST until possibly as late as 5pm PST. The new release has a lot of changes “under the hood” that make it more reliable and easier to update. The changes that will be […]

KBase App Replacement Coming Soon

KBase recently introduced a Software Development Kit (SDK) that simplifies the process of integrating analysis tools as KBase apps and also unifies the release and update process, making it easier for developers to support and upgrade KBase functionality. This will result in the KBase platform evolving more rapidly to better serve the requirements of our […]

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Research Highlights

Applying KBase to predict interspecies interactions with validation from transcriptomic data

In a cover article in the Journal of Cellular Physiology, KBase scientist Christopher Henry and his collaborators demonstrate strategies for constructing genome-scale metabolic networks that simulate two species in a microbial consortium exchanging metabolites to sustain life.

More about this research…

 

Using KBase to model central metabolism and energy biosynthesis across microbial life

In work published in BMC Genomics, KBase scientists developed new analysis tools that allowed them to more accurately predict biosynthetic energy yields by building core metabolic models representing 48 major phylogenetic microbial groups.

More about this research…