C M Kendziorski

Summary

Affiliation: University of Wisconsin
Country: USA

Publications

  1. ncbi Statistical methods for expression quantitative trait loci (eQTL) mapping
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin Madison, Madison, Wisconsin 53703, USA
    Biometrics 62:19-27. 2006
  2. ncbi Gene expression profiling of aging reveals activation of a p53-mediated transcriptional program
    Michael G Edwards
    Department of Genetics and Medical Genetics, University of Wisconsin, Madison, WI, USA
    BMC Genomics 8:80. 2007
  3. ncbi An efficient method for identifying statistical interactors in gene association networks
    Alina Andrei
    Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, 1300 University Avenue, Madison, WI 53706 1510, USA
    Biostatistics 10:706-18. 2009
  4. ncbi Mapping baroreceptor function to genome: a mathematical modeling approach
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin 53706, USA
    Genetics 160:1687-95. 2002
  5. ncbi The efficiency of pooling mRNA in microarray experiments
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, 6729 Medical Sciences Center, 1300 University Avenue, Madison, WI 53792, USA
    Biostatistics 4:465-77. 2003
  6. ncbi On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI 53703, USA
    Stat Med 22:3899-914. 2003
  7. ncbi On the utility of pooling biological samples in microarray experiments
    C Kendziorski
    Department of Biostatistics and Medical Informatics and McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI 53703, USA
    Proc Natl Acad Sci U S A 102:4252-7. 2005
  8. ncbi A review of statistical methods for expression quantitative trait loci mapping
    Christina Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, 1300 University Avenue 6729 MSC, Madison, WI 53706, USA
    Mamm Genome 17:509-17. 2006
  9. ncbi Genetic loci controlling breast cancer susceptibility in the Wistar-Kyoto rat
    H Lan
    McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, Wisconsin 53792, USA
    Genetics 157:331-9. 2001
  10. ncbi On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data
    M A Newton
    Department of Statistics, University of Wisconsin, Madison, WI 53792, USA
    J Comput Biol 8:37-52. 2001

Research Grants

  1. Statistical Methods for the Genomic Analysis of Gene Expression Data
    Christina Kendziorski; Fiscal Year: 2010
  2. Pooling Designs for Microarray Studies
    Christina Kendziorski; Fiscal Year: 2004
  3. Statistical Methods for the Genomic Analysis of Gene Expression Data
    Christina Kendziorski; Fiscal Year: 2007
  4. Statistical Methods for the Genomic Analysis of Gene Expression Data
    Christina Kendziorski; Fiscal Year: 2009

Collaborators

Detail Information

Publications20

  1. ncbi Statistical methods for expression quantitative trait loci (eQTL) mapping
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin Madison, Madison, Wisconsin 53703, USA
    Biometrics 62:19-27. 2006
    ..The MOM model is also the only one capable of finding two genome regions previously shown to be involved in diabetes...
  2. ncbi Gene expression profiling of aging reveals activation of a p53-mediated transcriptional program
    Michael G Edwards
    Department of Genetics and Medical Genetics, University of Wisconsin, Madison, WI, USA
    BMC Genomics 8:80. 2007
    ..We have used high density oligonucleotide arrays and novel statistical methods to identify specific transcriptional classes that may uncover biological processes that play a central role in mammalian aging...
  3. ncbi An efficient method for identifying statistical interactors in gene association networks
    Alina Andrei
    Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, 1300 University Avenue, Madison, WI 53706 1510, USA
    Biostatistics 10:706-18. 2009
    ..Practical advantages are demonstrated in analyses of data from a breast cancer study...
  4. ncbi Mapping baroreceptor function to genome: a mathematical modeling approach
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin 53706, USA
    Genetics 160:1687-95. 2002
    ..The phenotypes are then used in a quantitative trait loci (QTL) mapping study to identify a potential genetic basis of this controller...
  5. ncbi The efficiency of pooling mRNA in microarray experiments
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, 6729 Medical Sciences Center, 1300 University Avenue, Madison, WI 53792, USA
    Biostatistics 4:465-77. 2003
    ..As such, the results should be generally applicable to a number of technologies provided sufficient pre-processing and normalization methods are available and applied...
  6. ncbi On parametric empirical Bayes methods for comparing multiple groups using replicated gene expression profiles
    C M Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI 53703, USA
    Stat Med 22:3899-914. 2003
    ..The methodology is used in a study of mammary cancer in the rat, where four distinct patterns of expression are possible...
  7. ncbi On the utility of pooling biological samples in microarray experiments
    C Kendziorski
    Department of Biostatistics and Medical Informatics and McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI 53703, USA
    Proc Natl Acad Sci U S A 102:4252-7. 2005
    ..The realized benefits in this case do not outweigh the price paid for loss of individual specific information. Pooling is beneficial when many subjects are pooled, provided that independent samples contribute to multiple pools...
  8. ncbi A review of statistical methods for expression quantitative trait loci mapping
    Christina Kendziorski
    Department of Biostatistics and Medical Informatics, University of Wisconsin, 1300 University Avenue 6729 MSC, Madison, WI 53706, USA
    Mamm Genome 17:509-17. 2006
    ..In this article we review these principles and methods and discuss the open questions most likely to yield significant progress toward increasing the amount of meaningful information obtained from eQTL mapping experiments...
  9. ncbi Genetic loci controlling breast cancer susceptibility in the Wistar-Kyoto rat
    H Lan
    McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, Wisconsin 53792, USA
    Genetics 157:331-9. 2001
    ..In addition, we identified an interaction between Mcs8 and a region on chromosome 6 termed Mcsm1 (modifier of Mcs), which had no significant main effect on mammary cancer susceptibility in this genetic analysis...
  10. ncbi On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data
    M A Newton
    Department of Statistics, University of Wisconsin, Madison, WI 53792, USA
    J Comput Biol 8:37-52. 2001
    ..Significant gene expression changes are identified by deriving the posterior odds of change within a similar model. The methods are tested via simulation and are applied to a panel of Escherichia coli microarrays...
  11. ncbi Microarray analysis of BeWo and JEG3 trophoblast cell lines: identification of differentially expressed transcripts
    D W Burleigh
    Wisconsin National Primate Research Center, University of Wisconsin Medical School, 1220 Capitol Court, Madison, WI 53715 1299, USA
    Placenta 28:383-9. 2007
    ..These data suggest that BeWo and JEG3 cell lines, and perhaps other trophoblast cell lines, are sufficiently dissimilar from each other such that they will be differentially suited for specific experimental paradigms...
  12. ncbi Liver gene expression analysis reveals endoplasmic reticulum stress and metabolic dysfunction in SCD1-deficient mice fed a very low-fat diet
    Matthew T Flowers
    Department of Biochemistry, University of Wisconsin Madison, Madison, Wisconsin 53706, USA
    Physiol Genomics 33:361-72. 2008
    ....
  13. ncbi Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling
    Christine T Ferrara
    Sarah W Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, North Carolina, United States of America
    PLoS Genet 4:e1000034. 2008
    ..Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes...
  14. ncbi A statistical framework for expression quantitative trait loci mapping
    Meng Chen
    Pfizer Global Research and Development, Groton, Connecticut 06340, USA
    Genetics 177:761-71. 2007
    ..Evaluations are based on simulation studies and a study of diabetes in mice...
  15. ncbi A unified approach for simultaneous gene clustering and differential expression identification
    Ming Yuan
    School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive NW, Atlanta, Georgia 30332, USA
    Biometrics 62:1089-98. 2006
    ..The improvement over existing methods is illustrated in both our simulation results and a case study...
  16. ncbi Combined expression trait correlations and expression quantitative trait locus mapping
    Hong Lan
    Department of Biochemistry, University of Wisconsin, Madison, Wisconsin, USA
    PLoS Genet 2:e6. 2006
    ..The combined analysis is more sensitive compared with linkage mapping alone...
  17. ncbi Exenatide blocks JAK1-STAT1 in pancreatic beta cells
    Francesca M Couto
    Department of Medicine, University of Wisconsin, Madison, WI, USA
    Metabolism 56:915-8. 2007
    ..Thus, these findings suggest that Ex-4 treatment may also be beneficial in type 1 diabetes mellitus, where it may help protect beta cells from cytokine-induced cell death by inhibiting JAK1-STAT1...
  18. ncbi Identification of novel modifier loci of Apc Min affecting mammary tumor development
    Hua Wang
    Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin Madison, Madison, Wisconsin 53792, USA
    Cancer Res 67:11226-33. 2007
    ..None of these modifiers is associated with intestinal tumor susceptibility, which indicates that these modifiers act on tumor development in a tissue-specific manner...
  19. ncbi A gene expression network model of type 2 diabetes links cell cycle regulation in islets with diabetes susceptibility
    Mark P Keller
    Department of Biochemistry, University of Wisconsin, Madison, Wisconsin 53076, USA
    Genome Res 18:706-16. 2008
    ....
  20. ncbi Gene expression profiling in INS-1 cells overexpressing thioredoxin-interacting protein
    Alexandra H Minn
    Department of Medicine, University of Wisconsin-Madison, WI, USA
    Biochem Biophys Res Commun 336:770-8. 2005
    ..Thus, aside from regulating the cellular redox, TXNIP does modulate overall gene transcription and thereby may further enhance beta-cell death and impair insulin secretion...

Research Grants6

  1. Statistical Methods for the Genomic Analysis of Gene Expression Data
    Christina Kendziorski; Fiscal Year: 2010
    ..Successful completion of the proposed research will result in substantially improved statistical methods for these 2 important categories of genomic studies. ..
  2. Pooling Designs for Microarray Studies
    Christina Kendziorski; Fiscal Year: 2004
    ..abstract_text> ..
  3. Statistical Methods for the Genomic Analysis of Gene Expression Data
    Christina Kendziorski; Fiscal Year: 2007
    ..Successful completion of the proposed research will result in substantially improved statistical methods for these 2 important categories of genomic studies. ..
  4. Statistical Methods for the Genomic Analysis of Gene Expression Data
    Christina Kendziorski; Fiscal Year: 2009
    ..Successful completion of the proposed research will result in substantially improved statistical methods for these 2 important categories of genomic studies. ..