Rong Chen

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. ncbi Non-synonymous and synonymous coding SNPs show similar likelihood and effect size of human disease association
    Rong Chen
    Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America
    PLoS ONE 5:e13574. 2010
  2. ncbi FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease
    Rong Chen
    Stanford Center for Biomedical Informatics Research, 251 Cmpus Drive, Stanford, CA 94305, USA
    Genome Biol 9:R170. 2008
  3. ncbi GeneChaser: identifying all biological and clinical conditions in which genes of interest are differentially expressed
    Rong Chen
    Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
    BMC Bioinformatics 9:548. 2008
  4. ncbi ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression
    Jesse M Engreitz
    Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
    Bioinformatics 27:3317-8. 2011
  5. ncbi Compartmental localization and clinical relevance of MICA antibodies after renal transplantation
    Li Li
    Department of Pediatrics, Stanford University, Stanford, CA, USA 2 Department of Pathology, Stanford University, Stanford, CA 94304, USA
    Transplantation 89:312-9. 2010
  6. ncbi Phased whole-genome genetic risk in a family quartet using a major allele reference sequence
    Frederick E Dewey
    Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
    PLoS Genet 7:e1002280. 2011
  7. ncbi Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets
    Silpa Suthram
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
    PLoS Comput Biol 6:e1000662. 2010
  8. ncbi Content-based microarray search using differential expression profiles
    Jesse M Engreitz
    Department of Bioengineering, Stanford University School of Medicine, CA, USA
    BMC Bioinformatics 11:603. 2010
  9. ncbi Ontology-driven indexing of public datasets for translational bioinformatics
    Nigam H Shah
    Centre for Biomedical Informatics, School of Medicine, Stanford University, Stanford, CA 94305, USA
    BMC Bioinformatics 10:S1. 2009
  10. ncbi Identifying compartment-specific non-HLA targets after renal transplantation by integrating transcriptome and "antibodyome" measures
    Li Li
    Department of Pediatrics, Blood and Marrow Transplantation Division, Stanford University, 300 Pasteur Drive, Stanford, CA 94304, USA
    Proc Natl Acad Sci U S A 106:4148-53. 2009

Collaborators

Detail Information

Publications19

  1. ncbi Non-synonymous and synonymous coding SNPs show similar likelihood and effect size of human disease association
    Rong Chen
    Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America
    PLoS ONE 5:e13574. 2010
    ..Our results suggest that sSNPs are just as likely to be involved in disease mechanisms, so we recommend that sSNPs discovered from GWAS should also be examined with functional studies...
  2. ncbi FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease
    Rong Chen
    Stanford Center for Biomedical Informatics Research, 251 Cmpus Drive, Stanford, CA 94305, USA
    Genome Biol 9:R170. 2008
    ..We propose to use the more than 200,000 microarray studies in the Gene Expression Omnibus to systematically prioritize candidate SNPs from GWASs...
  3. ncbi GeneChaser: identifying all biological and clinical conditions in which genes of interest are differentially expressed
    Rong Chen
    Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
    BMC Bioinformatics 9:548. 2008
    ....
  4. ncbi ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression
    Jesse M Engreitz
    Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
    Bioinformatics 27:3317-8. 2011
    ..This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions...
  5. ncbi Compartmental localization and clinical relevance of MICA antibodies after renal transplantation
    Li Li
    Department of Pediatrics, Stanford University, Stanford, CA, USA 2 Department of Pathology, Stanford University, Stanford, CA 94304, USA
    Transplantation 89:312-9. 2010
    ..Antibodies (Ab) responses to major and minor human leukocyte antigen loci may impact graft survival after organ transplantation...
  6. ncbi Phased whole-genome genetic risk in a family quartet using a major allele reference sequence
    Frederick E Dewey
    Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University, Stanford, California, USA
    PLoS Genet 7:e1002280. 2011
    ..These ethnicity-specific, family-based approaches to interpretation of genetic variation are emblematic of the next generation of genetic risk assessment using whole-genome sequencing...
  7. ncbi Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets
    Silpa Suthram
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA
    PLoS Comput Biol 6:e1000662. 2010
    ....
  8. ncbi Content-based microarray search using differential expression profiles
    Jesse M Engreitz
    Department of Bioengineering, Stanford University School of Medicine, CA, USA
    BMC Bioinformatics 11:603. 2010
    ....
  9. ncbi Ontology-driven indexing of public datasets for translational bioinformatics
    Nigam H Shah
    Centre for Biomedical Informatics, School of Medicine, Stanford University, Stanford, CA 94305, USA
    BMC Bioinformatics 10:S1. 2009
    ..The key functionality of this system is to enable users to locate biomedical data resources related to particular ontology concepts...
  10. ncbi Identifying compartment-specific non-HLA targets after renal transplantation by integrating transcriptome and "antibodyome" measures
    Li Li
    Department of Pediatrics, Blood and Marrow Transplantation Division, Stanford University, 300 Pasteur Drive, Stanford, CA 94304, USA
    Proc Natl Acad Sci U S A 106:4148-53. 2009
    ..Correlation of the most significant non-HLA antibody responses with transplant health and dysfunction are currently underway...
  11. ncbi Clinical assessment incorporating a personal genome
    Euan A Ashley
    Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
    Lancet 375:1525-35. 2010
    ..The cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context...
  12. ncbi Performance comparison of whole-genome sequencing platforms
    Hugo Y K Lam
    Department of Genetics, Stanford University, Stanford, California, USA
    Nat Biotechnol 30:78-82. 2012
    ..Our results have important implications for understanding the accuracy and completeness of the genome sequencing platforms...
  13. ncbi Progressive histological damage in renal allografts is associated with expression of innate and adaptive immunity genes
    Maarten Naesens
    Division of Nephrology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
    Kidney Int 80:1364-76. 2011
    ..Thus, measurement of specific immune gene expression in protocol biopsies may be warranted to predict the development of subsequent chronic injury in histologically quiescent grafts and as a means to titrate immunosuppressive therapy...
  14. ncbi Personal omics profiling reveals dynamic molecular and medical phenotypes
    Rui Chen
    Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
    Cell 148:1293-307. 2012
    ..This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity...
  15. ncbi Translational bioinformatics in the cloud: an affordable alternative
    Joel T Dudley
    Program in Biomedical Informatics, Stanford University School of Medicine, 251 Campus Drive, Stanford, CA 94305, USA
    Genome Med 2:51. 2010
    ....
  16. ncbi Likelihood ratios for genome medicine
    Alexander A Morgan
    Department of Pediatrics and the Department of Medicine, Stanford University School of Medicine, 251 Campus Drive, MS 5415, Stanford, CA 94305 5479, USA
    Genome Med 2:30. 2010
    ..By using well-established methods of evidence based medicine, these very many parallel tests may be combined using likelihood ratios to report a post-test probability of disease for use in patient assessment...
  17. ncbi Performance comparison of exome DNA sequencing technologies
    Michael J Clark
    Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
    Nat Biotechnol 29:908-14. 2011
    ..We also compare exome sequencing and whole genome sequencing (WGS) of the same sample, demonstrating that exome sequencing can detect additional small variants missed by WGS...
  18. ncbi Interference of globin genes with biomarker discovery for allograft rejection in peripheral blood samples
    Li Li
    Pediatrics Department, Stanford University, Stanford, CA, USA
    Physiol Genomics 32:190-7. 2008
    ..Similar applications may exist for array-based biomarker discovery for other diseases associated with changes in leukocyte trafficking, activation, or function...
  19. ncbi Family history of prostate and breast cancer and the risk of prostate cancer in the PSA era
    Yen Ching Chen
    Department of Medicine, Channing Laboratory, Brigham and Women s Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA
    Prostate 68:1582-91. 2008
    ..A family history of prostate cancer (PCa) or breast cancer (BCa) has been associated with the risk of PCa, but the risks were inconsistent in terms of the affected family members, and data in the PSA era are limited...