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it - Information Technology

Methods and Applications of Informatics and Information Technology

Editor-in-Chief: Conrad, Stefan / Molitor, Paul

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Volume 58, Issue 3


Reconstructing single genomes from complex microbial communities

Dongwan D. Kang / Edward M. Rubin / Zhong Wang
  • Corresponding author
  • Department of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA
  • School of Natural Sciences, University of California at Merced, Merced, CA, 95343, USA
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Published Online: 2016-06-25 | DOI: https://doi.org/10.1515/itit-2016-0011


High throughput next generation sequencing technologies have enabled cultivation-independent approaches to study microbial communities in environmental samples. To date much of functional metagenomics has been limited to the gene or pathway level. Recent breakthroughs in metagenome binning have made it feasible to reconstruct high quality, individual microbial genomes from complex communities with thousands of species. In this review we aim to compare several automated metagenome binning software tools for their performance, and provide a practical guide for the metagenomics research community to carry out successful binning analyses.

Keywords: Computational genomics; computational biology; bioinformatics

ACM CCS: Applied computing →Life and medical sciences →Computational biology; Information systems →Information retrieval


The work was supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

About the article

Dongwan D. Kang

Dr. Dongwan D. Kang has completed his Ph.D. in Biostatistics from University of Pittsburgh and joined Lawrence Berkeley National Laboratory in 2012. He is an expert in data science and machine learning, and he authored several software packages in large-scale genomic data analyses.

Joint Genome Institute, Lawrence Berkeley National Laboratory, DOE, Walnut Creek, CA 94598, USA

Edward M. Rubin

Dr. Edward M. Rubin received his B.A. degree in physics from the University of California, San Diego, and both his Ph.D. in biophysics and his M.D. from the University of Rochester. He has been the director of the DOE Joint Genome Institute (JGI) since 2002. Dr. Rubin's research has involved the development and application of computational and biological approaches for studying genomes.

Joint Genome Institute, Lawrence Berkeley National Laboratory, DOE, Walnut Creek, CA 94598, USA

Zhong Wang

Dr. Zhong Wang is a career computational biologist and group leader for genome analysis at DOE Joint Genome Institute (JGI); he is also an adjunct professor at University of California at Merced. He received his B.S in Microbiology from Shandong University, China in 1994 and his Ph.D in Cell Biology from Duke University in 2004. He did his postdoc in the Institute of Genome Science and Policy at Duke University before becoming a research scientist and director of bioinformatics at Yale University Stem Cell Center in 2008. He joined JGI in 2009 and his research interests include transcriptomics, metagenomics, and high performance computing.

Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA

Accepted: 2016-03-11

Received: 2016-02-18

Published Online: 2016-06-25

Published in Print: 2016-06-28

Citation Information: it - Information Technology, Volume 58, Issue 3, Pages 133–139, ISSN (Online) 2196-7032, ISSN (Print) 1611-2776, DOI: https://doi.org/10.1515/itit-2016-0011.

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©2016 Dongwan D. Kang, Edward M. Rubin and Zhong Wang, published by De Gruyter GmbH Berlin/Boston.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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