Microbes – the single-celled organisms that dominate every ecosystem on Earth – have an amazing ability to feed on plant biomass and convert it into other chemical products. Tapping into this talent has the potential to revolutionize energy, medicine, environmental remediation, and many other fields. The success of this effort hinges in part on metagenomics, the emerging technology that enables researchers to read all the individual genomes of a sample microbial community at once. However, given that even a teaspoon of soil can contain billions of microbes, there is a great need to be able to cull the genomes of individual microbial species from a metagenomic sequence. Enter MaxBin, an automated software program for binning (sorting) the genomes of individual microbial species from metagenomic sequences. Developed at the U.S. Department of Energy (DOE)’s Joint BioEnergy Institute (JBEI), under the leadership of Dr. Steve Singer, who directs JBEI’s Microbial Communities Group, MaxBin facilitates the genomic analysis of uncultivated microbial populations that can hold the key to the production of new chemical materials, such as advanced biofuels or pharmaceutical drugs. “MaxBin automates the binning of assembled metagenomic scaffolds using an expectation-maximization algorithm after the assembly of metagenomic sequencing reads,” says Dr. Singer, a chemist who also holds an appointment with Berkeley Lab’s Earth Sciences Division. “Previous binning methods either required a significant amount of work by the user, or required a large number of samples for comparison. MaxBin requires only a single sample and is a push-button operation for users.” The key to the success of MaxBin is its expectation-maximization algorithm, which was developed by Dr. Yu-Wei Wu, a post-doctoral researcher in Dr.
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