Yingdong Zhao

Summary

Affiliation: National Institutes of Health
Country: USA

Publications

  1. pmc Gene expression deconvolution in clinical samples
    Yingdong Zhao
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
    Genome Med 2:93. 2010
  2. ncbi request reprint Molecular differentiation of high- and moderate-grade human prostate cancer by cDNA microarray analysis
    Carolyn J M Best
    Pathogenetics Unit, Laboratory of Pathology and Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
    Diagn Mol Pathol 12:63-70. 2003
  3. doi request reprint Conservation of genetic alterations in recurrent melanoma supports the melanoma stem cell hypothesis
    Marianna Sabatino
    Infectious Disease and Immunogenetics Section, Department of Transfusion Medicine, Warren G Magnuson Clinical Center, Biometrics Research Branch, National Cancer Institute, NIH, Bethesda, Maryland 20892 1184, USA
    Cancer Res 68:122-31. 2008
  4. pmc Analysis of gene expression data using BRB-ArrayTools
    Richard Simon
    Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
    Cancer Inform 3:11-7. 2007
  5. pmc "Sequencing-grade" screening for BRCA1 variants by oligo-arrays
    Alessandro Monaco
    Department of Transfusion Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA
    J Transl Med 6:64. 2008
  6. pmc MicroRNA expression differentiates histology and predicts survival of lung cancer
    Maria Teresa Landi
    Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, Maryland 20892 7236, USA
    Clin Cancer Res 16:430-41. 2010
  7. doi request reprint How large a training set is needed to develop a classifier for microarray data?
    Kevin K Dobbin
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Rockville, Maryland 20852, USA
    Clin Cancer Res 14:108-14. 2008
  8. pmc Strengths and limitations of laboratory procedures for microRNA detection
    Jill Koshiol
    Infections and Immunepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, Room 7070, Rockville, MD 20852 7248, USA
    Cancer Epidemiol Biomarkers Prev 19:907-11. 2010
  9. pmc Sequential gene profiling of basal cell carcinomas treated with imiquimod in a placebo-controlled study defines the requirements for tissue rejection
    Monica C Panelli
    Immunogenetics Section, Department of Transfusion Medicine, Clinical Center National Institutes of Health, Bethesda, MD 20892, USA
    Genome Biol 8:R8. 2007
  10. pmc Development and validation of predictive indices for a continuous outcome using gene expression profiles
    Yingdong Zhao
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA Email
    Cancer Inform 9:105-14. 2010

Detail Information

Publications20

  1. pmc Gene expression deconvolution in clinical samples
    Yingdong Zhao
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
    Genome Med 2:93. 2010
    ..Consequently, the deconvolution approach can be useful in the analysis of mixtures of cell populations in clinical samples...
  2. ncbi request reprint Molecular differentiation of high- and moderate-grade human prostate cancer by cDNA microarray analysis
    Carolyn J M Best
    Pathogenetics Unit, Laboratory of Pathology and Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
    Diagn Mol Pathol 12:63-70. 2003
    ..We suggest that these data provide insight into the molecular nature of clinically aggressive prostate cancer...
  3. doi request reprint Conservation of genetic alterations in recurrent melanoma supports the melanoma stem cell hypothesis
    Marianna Sabatino
    Infectious Disease and Immunogenetics Section, Department of Transfusion Medicine, Warren G Magnuson Clinical Center, Biometrics Research Branch, National Cancer Institute, NIH, Bethesda, Maryland 20892 1184, USA
    Cancer Res 68:122-31. 2008
    ..Our study provides important insights about the dynamics of cancer progression and supports the development of targeted anticancer therapies aimed against stable genetic factors that are maintained throughout the end stage of disease...
  4. pmc Analysis of gene expression data using BRB-ArrayTools
    Richard Simon
    Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
    Cancer Inform 3:11-7. 2007
    ....
  5. pmc "Sequencing-grade" screening for BRCA1 variants by oligo-arrays
    Alessandro Monaco
    Department of Transfusion Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA
    J Transl Med 6:64. 2008
    ..This system is particularly useful for the screening of long genomic regions with relatively infrequent but clinically relevant variants, while drastically cutting time and costs in comparison to high-throughput sequencing...
  6. pmc MicroRNA expression differentiates histology and predicts survival of lung cancer
    Maria Teresa Landi
    Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Department of Health and Human Services, Bethesda, Maryland 20892 7236, USA
    Clin Cancer Res 16:430-41. 2010
    ..The molecular drivers that determine histology in lung cancer are largely unknown. We investigated whether microRNA (miR) expression profiles can differentiate histologic subtypes and predict survival for non-small cell lung cancer...
  7. doi request reprint How large a training set is needed to develop a classifier for microarray data?
    Kevin K Dobbin
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Rockville, Maryland 20852, USA
    Clin Cancer Res 14:108-14. 2008
    ..The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging...
  8. pmc Strengths and limitations of laboratory procedures for microRNA detection
    Jill Koshiol
    Infections and Immunepidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, Room 7070, Rockville, MD 20852 7248, USA
    Cancer Epidemiol Biomarkers Prev 19:907-11. 2010
    ..MicroRNAs (miR) are endogenous, noncoding RNAs involved in many cellular processes and have been associated with the development and progression of cancer. There are many different ways to evaluate miRs...
  9. pmc Sequential gene profiling of basal cell carcinomas treated with imiquimod in a placebo-controlled study defines the requirements for tissue rejection
    Monica C Panelli
    Immunogenetics Section, Department of Transfusion Medicine, Clinical Center National Institutes of Health, Bethesda, MD 20892, USA
    Genome Biol 8:R8. 2007
    ..We hypothesized that the characterization of the early transcriptional events induced by imiquimod may provide insights about immunological events preceding acute tissue and/or tumor rejection...
  10. pmc Development and validation of predictive indices for a continuous outcome using gene expression profiles
    Yingdong Zhao
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA Email
    Cancer Inform 9:105-14. 2010
    ..We have developed a plug-in for BRB-ArrayTools that implements the LAR and the LASSO algorithms with complete cross-validation...
  11. pmc Evaluation of normalization methods for two-channel microRNA microarrays
    Yingdong Zhao
    Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
    J Transl Med 8:69. 2010
    ..Findings from previous studies have sometimes been inconclusive or contradictory. Further studies to determine optimal normalization methods for miR microarrays are needed...
  12. pmc An adaptive method for cDNA microarray normalization
    Yingdong Zhao
    Biometric Research Branch, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA
    BMC Bioinformatics 6:28. 2005
    ..These assumptions can be inappropriate for custom arrays or arrays in which the reference RNA is very different from the experimental samples...
  13. pmc Selection and validation of endogenous reference genes using a high throughput approach
    Ping Jin
    Immunogenetics Section, Department of Transfusion Medicine, Clinical Center, NIH Bethesda, MD 20892, USA
    BMC Genomics 5:55. 2004
    ..Whether this assumption is correct it is, however, still matter of debate. In this study, we searched for stably expressed genes in 384 cDNA array hybridization experiments encompassing different tissues and cell lines...
  14. pmc A comparison of phase II study strategies
    Sally Hunsberger
    Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland 20892, USA
    Clin Cancer Res 15:5950-5. 2009
    ..In this article, we compare different phase II study strategies to determine the most efficient drug development path in terms of number of patients and length of time to conclusion of drug efficacy on overall survival...
  15. pmc Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness
    Ena Wang
    Immunogenetics Section, Department of Transfusion Medicine, Clinical Center, NIH, Bethesda, Maryland 20892, USA
    Cancer Res 62:3581-6. 2002
    ..001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition...
  16. ncbi request reprint Common cancer biomarkers
    Christopher F Basil
    Department of Transfusion Medicine, Warren G Magnuson Clinical Center, National Cancer Institute, NIH, Bethesda, Maryland 20892 1184, USA
    Cancer Res 66:2953-61. 2006
    ....
  17. ncbi request reprint Gene Set Expression Comparison kit for BRB-ArrayTools
    Xiaojiang Xu
    Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
    Bioinformatics 24:137-9. 2008
    ..AVAILABILITY: Gene Set Expression Comparison kit is freely available as a module of BRB-ArrayTools for non-commercial users. BRB-ArrayTools is available at http://linus.nci.nih.gov/BRB-ArrayTools.html...
  18. doi request reprint Combining positional scanning peptide libraries, HLA-DR transfectants and bioinformatics to dissect the epitope spectrum of HLA class II cross-restricted CD4+ T cell clones
    Mireia Sospedra
    Cellular Immunology Section, Neuroimmunology Branch, NINDS, National Institutes of Health, Bethesda, Maryland 20892, USA
    J Immunol Methods 353:93-101. 2010
    ..In contrast, the use of B cell lines expressing single HLA class II molecules as APCs instead of autologous peripheral blood mononuclear cells markedly improves the capacity to identify target peptides for this type of T cells...
  19. pmc Recognition of conserved amino acid motifs of common viruses and its role in autoimmunity
    Mireia Sospedra
    Cellular Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
    PLoS Pathog 1:e41. 2005
    ..Our data suggest that repeated infections with common pathogenic and even nonpathogenic viruses could expand T cells specific for conserved protein domains that are able to cross-react with tissue-derived and ubiquitous autoantigens...
  20. doi request reprint Artificial intelligence methods for predicting T-cell epitopes
    Yingdong Zhao
    National Cancer Institute, National Institutes of Health, Rockville, MD, USA
    Methods Mol Biol 409:217-25. 2007
    ..For predicting T-cell epitopes for an MHC class II-restricted TCC, we built a shift model that integrated MHC-binding data and data from T-cell proliferation assay against a combinatorial library of peptide mixtures...