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Zhong Wang

Zhong Wang

Zhong Wang, DOE Joint Genome Institute

Research in the Analysis R&D group focuses on developing new bioinformatics solutions to support JGI in adopting new genomics technologies, scaling up genomics analysis to peta-bases, and enabling data-driven science. This is a group of computational biologists, bioinformaticians, computer scientists and biostatisticians. Through collaborations with internal and external scientists, the Wang group has developed customized data analyses and software to enable “grand-scale” scientific projects. These solutions include large-scale genome variants analyses, next-generation transcriptome de novo assembly, metagenome and metatranscriptome assembly, Hadoop based on sequence analysis framework, etc. For example, this group was responsible for the tera-base scale data analysis in the cow rumen and sheep rumen metagenome projects.

Standing at the intersection between the rapid development of genome and computational technologies, in the coming years the Wang group will continue its effort to explore new genome and computational technologies (NanoPore, GPU, Cloud etc) and their applications in solving DOE’s most challenging problems.

Education

  • PhD Cell Biology. Duke University
  • MS Developmental Biology, Chinese Academy of Sciences, Shanghai, China
  • BS Microbiology, Shandong University, Ji’nan, China

Software

  • ALE, assembly quality evaluation software based on Bayesian statistics
  • BioPig, a Hadoop-based data analytic framework
  • MetaBAT, an automatic metagenome binning software

    • Selected Publications

    1. Weibing Shi, Christina Moon, Sinead Leahy, Dongwan Kang, Jeff Froula, Sandra Kittelmann, Christina Fan, Samuel Deutsch, Dragana Gagic, Henning Seedorf, William Kelly, Renee Atua, Carrie Sang, Priya Soni, Dong Li, Cesar Pinares-Patiño, John McEwan, Peter Janssen, Feng Chen, Axel Visel, Zhong Wang, Graeme Attwood, Edward Rubin. Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome Genome Research (2014). gr. 168245.113
    2. Jeffrey A. Martin, Nicole V. Johnson, Stephen M. Gross, James Schnable, Xiandong Meng, Mei Wang, Devin Coleman-Derr, Erika Lindquist, Chia-Lin Wei, Shawn Kaeppler, Feng Chen, and Zhong Wang. A near complete snapshot of the Zea mays seedling transcriptome revealed from ultra-deep sequencing. Scientific Reports (2014). DOI: 10.1038/srep04519.
    3. Byrne RT, Klingele AJ, Cabot EL, Schackwitz WS, Martin JM, Martin J, Wang Z, Wood EA, Pennacchio C, Pennacchio LA, Perna NT, Battista JR, and Cox MM. Evolution of Extreme Resistance to Ionizing Radiation via Genetic Adaptation of DNA Repair. eLife (2014). In press.
    4. Nordberg H, Bhatia K, Wang K, Wang Z. BioPig: A Hadoop-based Analytic Toolkit for Large-Scale Sequence Data. Bioinformatics (2013). doi:10.1093/bioinformatics/btt528
    5. Scott Clark, Rob Egan, Peter I. Frazier, and Zhong Wang. ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies. Bioinformatics (2013). doi: 10.1093/bioinformatics/bts723
    6. Koren S, Schatz MC, Walenz BP, Martin J, Howard JT, Ganapathy G, Wang Z, Rasko DA, McCombie WR, Jarvis ED, Phillippy AM. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nature biotechnology. 2012 Jul 1
    7. Martin J. and Wang Z. Next generation transcriptome assembly. Nature Reviews Genetics. 2011;12(10):671-82.
    8. Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, Luo S, Clark DS, Chen F, Zhang T, Mackie RI, Pennacchio LA, Tringe SG, Visel A, Woyke T, Wang Z, Rubin EM. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science. 2011 Jan 28;331(6016):463-7
    9. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics. 2009 Jan;10(1):57-63
    10. Nagalakshmi U, Wang Z(co-first), Waern K, Shou C, Raha D, Gerstein M, Snyder M. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science. 2008 Jun 6;320(5881):1344-9
    11. Wang Z, Willard HF, Mukherjee S, Furey TS. Evidence of influence of genomic DNA sequence on human X chromosome inactivation. PLoS Computational Biology. 2006 Sep 1;2(9):e113
    12. Wang Z, Lin H. Nanos maintains germline stem cell self-renewal by preventing differentiation. Science. 2004 Mar 26;303(5666):2016-9