Hee Shin Kim Hee Shin Kim is a bioinformatician at the Center for Human Genome Variation. His major responsibilities include new software development and maintenance of specific areas of the next generation sequencing analysis pipeline. He is also focusing on developing and implementing innovative computational approaches for the analysis of large sequence datasets from NGS technologies.

Selected Publications:

1. Kim HS, Murphy T, Xia J, Caragea D, Park Y, Beeman RW, Lorenzen MD, Manak JR, Butcher S, and Brown S. BeetleBase in 2010: revisions to provide comprehensive genomic information for Tribolium castaneum Nucleic Acid Res. 2010, 38(Database issue):D437.
2. Caetano-Anollés G, Yafremava LS, H Gee, Caetano-Anollees D, Kim HS, Mittenthal JE. The origin and evolution of modern metabolism. International J Biochemistry & Cell Biology 2009, 41:285-297.
3. Caetano-Anolles G, SunF-J, Wang M, Yafremava LS, Harish A, Kim HS, Knudsen V, Caetano-Anolles D, Mittenthal JE. Origins and evolution of modern biochemistry: insights from genomes and molecular structure. Frontiers in Bioscience 2008, 13: 5212-5240.
4. Caetano-Anollés G, Kim HS, Mittenthal JE. The origin of modern metabolic networks inferred from phylogenomic analysis of protein architecture. Proc. Natl. Acad. Sci. USA 2007, 104:9358-9363.
5. Kim HS, Mittenthal JE, Caetano-Anollés G. MANET: tracing evolution of protein architecture in metabolic networks. BMC Bioinformatics 2006, 7:351. 

Jessica M. Maia Jessica M. Maia, Ph.D is a computational biologist at the Center for Human Genome Variation. She oversees the computational processes from which human variation is identified from whole genome sequencing. She also performs bioinformatic and statistical analyses for various projects in the Center.

 

Quanli Wang   Quanli Wang is a bioinformatician II at the Center for Human Genome Variation.  His previous work involved high-performance cluster/GPU computing for large statistical models and imaging analysis and algorithm development for single cell biological image data. At CHGV, Quanli will be focusing on the next generation sequencing analysis pipeline. He will also work on a variety of projects within the center.

Selected Publications 

1. Q. Wang, M. West. Model-controlled flooding with applications to image reconstruction and segmentation. Journal of Electronic Imaging, 21(2012).  pp. 023020
   
2. Q. Wang, J. Niemi, C.H Tan, L. You, M. West. Image segmentation and dynamic lineage analysis in single-cell fluorescent microscopy. Cytometry A 77(2010). 101-110.
3. M. Suchard, Q. Wang, C. Chan, J. Frelinger, A. Cron and M. West. "Understanding GPU programming for statistical computation: Studies in massively parallel massive mixtures." Journal of Computational and Graphical Statistics 19 (2010): 419-438.
4. M. L. Gatza, J.E. Lucus, W.T. Barry, J.W. Kim, Q. Wang, M.D. Crawford, M.B. Datto, M. Kelley, B. Mathey-Prevot, A. Potti and J.R. Nevins. "A pathway-based classification of human breast cancer." PNAS 107(15) (2010), 6994-6999.
5. J. Chang, C. Carvalho, S. Mori, A. Bild, Q. Wang, M. West, J. Nevins (2009). Decomposing cellular signaling pathways into functional units: A genomic strategy. Molecular Cell 34.1, 104-114.
6. C. Carvalho, J. Lucas, Q. Wang, J. T. Chang, J.R. Nevins, M. West (2008). High-Dimensional Sparse Factor Modelling: Applications in Gene Expression Genomics. Journal of the American Statistical Association 103 (2008): 1438-1456.
7. Q. Wang, C. Carvalho, J.E. Lucas and M. West (2007). BFRM: Bayesian factor regression modelling. Bulletin of the International Society for Bayesian Analysis 14 (2007): 4-5.
8. J. Lucas, C. Carvalho, Q. Wang, A. Bild, J.R. Nevins and M. West. Sparse statistical modelling in gene expression genomics. Bayesian Inference for Gene Expression and Proteomics (2006): 155-176.
9. A.H. Bild, G. Yao, J.T. Chang, Q. Wang, A. Potti, D. Chasse, M. Joshi, D. Harpole, J.M. Lancaster, A. Berchuck, J.A. Olson, J.R. Marks, H.K. Dressman, M.West and J.R. Nevins. "Oncogenic pathway signatures in human cancers as a guide to targeted therapies." Nature 439 (2006): 353-357.

Zhong Ren   Zhong is an accomplished Web and Java developer with a background in bioinformatics research programming.  He previously worked on the development team for the Integrated Genome Browser.  At CHGV, Zhong is working with the Bioinformatics team on developing the next generation sequencing analysis pipeline.  In addition he will work with Min He in the computational development of the ATAV (Analysis Tool for Annotated Variants) toolset.