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Defining the Healthy Human Microbiome


The human microbiome—the microorganisms that colonize the human body by the trillions—plays a fundamental role health and disease. To understand the microbiome’s exact functions, good and bad, the microbial make-up of healthy humans have been mapped for the first time. » Read More

Billions of Genes and Counting!


The Integrated Microbial Genomes with Microbiome Samples data management system, which supports the analysis of microbial communities sequenced by the DOE's Joint Genome Institute (JGI) currently contains more than 3 billion microbial genes—more than any other similar system in the world. » Read More

The Biosciences Computing Group (BCG) is part of the Computational Research Division (CRD) at DOE’s Lawrence Berkeley National Laboratory (LBNL). BCG's mission is to address key data management challenges caused by the massive increase in the amount and range of biological data, the difficulty of quantifying the quality of data generated using inherently imprecise tools and techniques, and the high complexity of integrating data residing in diverse and sometimes poorly correlated repositories. BCG's strategy involves using existing database technologies and analysis methods, adapted as needed to a specific application, in order to address immediate biological data management and bioinformatics requirements. Critical data management and analysis problems that cannot be resolved using existing technologies and methods are pursued as part of longer term R&D activities.

In partnership with scientists of the Microbial Genome and Metagenome Programs at the DOE Joint Genome Institute (JGI), BCG engineers and computer scientists have developed and maintained a suite of microbial genome and metagenome data management and analysis systems, called the Integrated Microbial Genomes (IMG) systems. These systems have a large community of scientific users worldwide, and have provided support for the completion of thousands of microbial genome and metagenome studies. BCG’s activities are mainly of a production nature, whereby the key challenges regard the regular content and software updates of the IMG systems while coping with a rapid increase in the number and size of new microbial genome and metagenome datasets.

Co-Group Leads: I-Min Chen and Ken Chu