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Vivian G. Cheung

Bio: Vivian G. Cheung is an academic researcher from University of Michigan. The author has contributed to research in topics: Gene & Regulation of gene expression. The author has an hindex of 39, co-authored 74 publications receiving 10446 citations. Previous affiliations of Vivian G. Cheung include Howard Hughes Medical Institute & Children's Hospital of Philadelphia.


Papers
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Journal ArticleDOI
TL;DR: Implementation of a new toxicity testing paradigm firmly based on human biology by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters.
Abstract: With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology.

1,398 citations

Journal ArticleDOI
12 Aug 2004-Nature
TL;DR: This work used microarrays to measure gene expression levels and performed genome-wide linkage analysis for expression levels of 3,554 genes in 14 large families to localize the genetic determinants of these quantitative traits in humans.
Abstract: Natural variation in gene expression is extensive in humans and other organisms, and variation in the baseline expression level of many genes has a heritable component. To localize the genetic determinants of these quantitative traits (expression phenotypes) in humans, we used microarrays to measure gene expression levels and performed genome-wide linkage analysis for expression levels of 3,554 genes in 14 large families. For approximately 1,000 expression phenotypes, there was significant evidence of linkage to specific chromosomal regions. Both cis- and trans-acting loci regulate variation in the expression levels of genes, although most act in trans. Many gene expression phenotypes are influenced by several genetic determinants. Furthermore, we found hotspots of transcriptional regulation where significant evidence of linkage for several expression phenotypes (up to 31) coincides, and expression levels of many genes that share the same regulatory region are significantly correlated. The combination of microarray techniques for phenotyping and linkage analysis for quantitative traits allows the genetic mapping of determinants that contribute to variation in human gene expression.

1,246 citations

Journal ArticleDOI
John Douglas Mcpherson1, Marco A. Marra1, Marco A. Marra2, LaDeana W. Hillier1, Robert H. Waterston1, Asif T. Chinwalla1, John W. Wallis1, Mandeep Sekhon1, Kristine M. Wylie1, Elaine R. Mardis1, Richard K. Wilson1, Robert S. Fulton1, Tamara A. Kucaba1, Caryn Wagner-McPherson1, William B. Barbazuk1, Simon G. Gregory3, Sean Humphray3, Lisa French3, R Evans3, Graeme Bethel3, Adam Whittaker3, Jane L. Holden3, Owen T. McCann3, Andrew Dunham3, Carol Soderlund4, Carol Scott3, David R. Bentley3, Gregory D. Schuler5, Hsiu Chuan Chen5, Wonhee Jang5, Eric D. Green5, Jacquelyn R. Idol5, Valerie Maduro5, Kate Montgomery6, Eunice Lee6, Ashley Miller6, Suzanne Emerling6, Raju Kucherlapati6, Richard A. Gibbs7, Steve Scherer7, J. Harley Gorrell7, Erica Sodergren7, Kerstin P. Clerc-Blankenburg7, Paul E. Tabor7, S. Naylor8, Dawn Garcia8, J. de Jong9, J. de Jong10, J. de Jong11, Joseph J. Catanese11, Joseph J. Catanese9, Joseph J. Catanese10, Norma J. Nowak11, Kazutoyo Osoegawa10, Kazutoyo Osoegawa11, Kazutoyo Osoegawa9, Shizhen Qin12, Lee Rowen12, Anuradha Madan12, Monica Dors12, Leroy Hood12, Barbara J. Trask13, Cynthia Friedman13, Hillary Massa13, Vivian G. Cheung14, Ilan R. Kirsch5, Thomas Reid5, Raluca Yonescu5, Jean Weissenbach, Thomas Brüls, Roland Heilig, Elbert Branscomb15, Anne S. Olsen15, Norman A. Doggett15, Jan Fang Cheng15, Trevor Hawkins15, Richard M. Myers16, Jin Shang16, Lucía Ramírez16, Jeremy Schmutz16, Olivia Velasquez16, Kami Dixon16, Nancy E. Stone16, David R. Cox16, David Haussler17, W. James Kent17, Terrence S. Furey17, Sanja Rogic17, Scot Kennedy17, Steven J.M. Jones2, André Rosenthal5, Gaiping Wen5, Markus Schilhabel5, Gernot Gloeckner5, Gerald Nyakatura5, Reiner Siebert18, Brigitte Schlegelberger18, Julie R. Korenberg19, Xiao Ning Chen19, Asao Fujiyama, Masahira Hattori, Atsushi Toyoda, Tetsushi Yada, Hong Seok Park, Yoshiyuki Sakaki, Nobuyoshi Shimizu20, Shuichi Asakawa20, Kazuhiko Kawasaki20, Takashi Sasaki20, Ai Shintani20, Atsushi Shimizu20, Kazunori Shibuya20, Jun Kudoh20, Shinsei Minoshima20, Juliane Ramser21, Peter Seranski21, Céline Hoff21, Annemarie Poustka21, Richard Reinhardt21, Hans Lehrach21 
15 Feb 2001-Nature
TL;DR: The construction of the whole-genome bacterial artificial chromosome (BAC) map and its integration with previous landmark maps and information from mapping efforts focused on specific chromosomal regions are reported.
Abstract: The human genome is by far the largest genome to be sequenced, and its size and complexity present many challenges for sequence assembly. The International Human Genome Sequencing Consortium constructed a map of the whole genome to enable the selection of clones for sequencing and for the accurate assembly of the genome sequence. Here we report the construction of the whole-genome bacterial artificial chromosome (BAC) map and its integration with previous landmark maps and information from mapping efforts focused on specific chromosomal regions. We also describe the integration of sequence data with the map.

876 citations

Journal ArticleDOI
TL;DR: The building and use of two microarray facilities in academic settings are described and the advantages and disadvantages of components and approaches are commented on, and a protocol for hybridization is provided.
Abstract: There are a variety of options for making microarrays and obtaining microarray data. Here, we describe the building and use of two microarray facilities in academic settings. In addition to specifying technical detail, we comment on the advantages and disadvantages of components and approaches, and provide a protocol for hybridization. The fact that we are now making and using microarrays to answer biological questions demonstrates that the technology can be implemented in a university environment.

738 citations

Journal ArticleDOI
TL;DR: There is evidence for familial aggregation of expression phenotype by comparing variation among unrelated individuals, among siblings within families and between monozygotic twins, which suggests that there is a genetic contribution to polymorphic variation in the level of gene expression.
Abstract: The sequencing of the human genome has resulted in greater attention to genetic variation among individuals, and variation at the DNA sequence level is now being extensively studied. At the same time, it has become possible to study variation at the level of gene expression by various methods. At present, it is largely unknown how widespread this variation in transcript levels is over the entire genome and to what extent individual differences in expression level are genetically determined. In the present study, we used lymphoblastoid cells to examine variation in gene expression and identified genes whose transcript levels differed greatly among unrelated individuals. We also found evidence for familial aggregation of expression phenotype by comparing variation among unrelated individuals, among siblings within families and between monozygotic twins. These observations suggest that there is a genetic contribution to polymorphic variation in the level of gene expression.

659 citations


Cited by
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Journal ArticleDOI
Eric S. Lander1, Lauren Linton1, Bruce W. Birren1, Chad Nusbaum1  +245 moreInstitutions (29)
15 Feb 2001-Nature
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

22,269 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu.
Abstract: As vertebrate genome sequences near completion and research refocuses to their analysis, the issue of effective genome annotation display becomes critical. A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu. This browser displays assembly contigs and gaps, mRNA and expressed sequence tag alignments, multiple gene predictions, cross-species homologies, single nucleotide polymorphisms, sequence-tagged sites, radiation hybrid data, transposon repeats, and more as a stack of coregistered tracks. Text and sequence-based searches provide quick and precise access to any region of specific interest. Secondary links from individual features lead to sequence details and supplementary off-site databases. One-half of the annotation tracks are computed at the University of California, Santa Cruz from publicly available sequence data; collaborators worldwide provide the rest. Users can stably add their own custom tracks to the browser for educational or research purposes. The conceptual and technical framework of the browser, its underlying MYSQL database, and overall use are described. The web site currently serves over 50,000 pages per day to over 3000 different users.

9,605 citations

Journal ArticleDOI
TL;DR: This protocol provides a workflow for genome-independent transcriptome analysis leveraging the Trinity platform and presents Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes.
Abstract: De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

6,369 citations

Journal ArticleDOI
TL;DR: MiRNA-expression profiling of human tumours has identified signatures associated with diagnosis, staging, progression, prognosis and response to treatment and has been exploited to identify miRNA genes that might represent downstream targets of activated oncogenic pathways, or that target protein-coding genes involved in cancer.
Abstract: MicroRNA (miRNA ) alterations are involved in the initiation and progression of human cancer. The causes of the widespread differential expression of miRNA genes in malignant compared with normal cells can be explained by the location of these genes in cancer-associated genomic regions, by epigenetic mechanisms and by alterations in the miRNA processing machinery. MiRNA-expression profiling of human tumours has identified signatures associated with diagnosis, staging, progression, prognosis and response to treatment. In addition, profiling has been exploited to identify miRNA genes that might represent downstream targets of activated oncogenic pathways, or that target protein- coding genes involved in cancer.

6,345 citations