Shili Lin

Summary

Publications

  1. doi request reprint Integration of ranked lists via cross entropy Monte Carlo with applications to mRNA and microRNA Studies
    Shili Lin
    Department of Statistics, The Ohio State University, Columbus, Ohio 43210 1247, USA
    Biometrics 65:9-18. 2009
  2. pmc Probe signal correction for differential methylation hybridization experiments
    Dustin P Potter
    Human Cancer Genetics Program, OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
    BMC Bioinformatics 9:453. 2008
  3. ncbi request reprint Modeling and analysis of multi-library, multi-group SAGE data with application to a study of mouse cerebellum
    Zailong Wang
    Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio 43210, USA
    Biometrics 63:777-86. 2007
  4. doi request reprint Differential methylation hybridization: profiling DNA methylation with a high-density CpG island microarray
    Pearlly S Yan
    Human Cancer Genetics Program, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
    Methods Mol Biol 507:89-106. 2009
  5. doi request reprint MicroRNAs modulate the chemosensitivity of tumor cells
    Paul E Blower
    Program of Pharmacogenomics, Department of Pharmacology, Ohio State University, 333 West Tenth Street, Columbus, OH 43210, USA
    Mol Cancer Ther 7:1-9. 2008
  6. ncbi request reprint Microsatellites versus Single-Nucleotide Polymorphisms in confidence interval estimation of disease loci
    Charalampos Papachristou
    Department of Statistics, Ohio State University, Columbus, 43210, USA
    Genet Epidemiol 30:3-17. 2006
  7. pmc Integrative genome-wide chromatin signature analysis using finite mixture models
    Cenny Taslim
    Department of Statistics, The Ohio State University, Columbus, Ohio 43210, USA
    BMC Genomics 13:S3. 2012
  8. doi request reprint Analyzing ChIP-seq data: preprocessing, normalization, differential identification, and binding pattern characterization
    Cenny Taslim
    Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH, USA
    Methods Mol Biol 802:275-91. 2012
  9. pmc Comparisons of methods for linkage analysis and haplotype reconstruction using extended pedigree data
    Shili Lin
    Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA
    BMC Genet 6:S76. 2005
  10. pmc Breast cancer-associated fibroblasts confer AKT1-mediated epigenetic silencing of Cystatin M in epithelial cells
    Huey Jen L Lin
    Division of Medical Technology, School of Allied Medical Professions, Human Cancer Genetics Program, The Ohio State University, Columbus, Ohio 43210, USA
    Cancer Res 68:10257-66. 2008

Collaborators

Detail Information

Publications43

  1. doi request reprint Integration of ranked lists via cross entropy Monte Carlo with applications to mRNA and microRNA Studies
    Shili Lin
    Department of Statistics, The Ohio State University, Columbus, Ohio 43210 1247, USA
    Biometrics 65:9-18. 2009
    ..Extensive simulation studies were performed to assess the performance of the method. With satisfactory simulation results, the method was applied to the microRNA and mRNA problems to illustrate its utility...
  2. pmc Probe signal correction for differential methylation hybridization experiments
    Dustin P Potter
    Human Cancer Genetics Program, OSU Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
    BMC Bioinformatics 9:453. 2008
    ..Hybridization effects related to probe-sequence composition and DNA dye-probe interactions have been observed in differential methylation hybridization (DMH) microarray experiments as well as other effects inherent to the DMH protocol...
  3. ncbi request reprint Modeling and analysis of multi-library, multi-group SAGE data with application to a study of mouse cerebellum
    Zailong Wang
    Mathematical Biosciences Institute, The Ohio State University, Columbus, Ohio 43210, USA
    Biometrics 63:777-86. 2007
    ..Our gene ontology (GO) analysis of the genes selected classifies them into several GO categories, which appear to be functionally relevant to aging...
  4. doi request reprint Differential methylation hybridization: profiling DNA methylation with a high-density CpG island microarray
    Pearlly S Yan
    Human Cancer Genetics Program, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
    Methods Mol Biol 507:89-106. 2009
    ..As we continue to update our analysis algorithm and approaches to integrate high-throughput methylation data with other large-scale data types, we will make these new computation protocols available through the GenePattern platform...
  5. doi request reprint MicroRNAs modulate the chemosensitivity of tumor cells
    Paul E Blower
    Program of Pharmacogenomics, Department of Pharmacology, Ohio State University, 333 West Tenth Street, Columbus, OH 43210, USA
    Mol Cancer Ther 7:1-9. 2008
    ..Ten of those microRNAs have already been implicated in cancer biology. Our results support a substantial role for microRNAs in anticancer drug response, suggesting novel potential approaches to the improvement of chemotherapy...
  6. ncbi request reprint Microsatellites versus Single-Nucleotide Polymorphisms in confidence interval estimation of disease loci
    Charalampos Papachristou
    Department of Statistics, Ohio State University, Columbus, 43210, USA
    Genet Epidemiol 30:3-17. 2006
    ..Finally, it is interesting (although not surprising) to note that, should one wish to perform a quick preliminary genome screening, then the two-point CSI procedure would be a preferred, computationally cost-effective choice...
  7. pmc Integrative genome-wide chromatin signature analysis using finite mixture models
    Cenny Taslim
    Department of Statistics, The Ohio State University, Columbus, Ohio 43210, USA
    BMC Genomics 13:S3. 2012
    ..Around 5% (431 regions) of these correlated regions do not overlap with any transcripts or regulatory regions suggesting that these might be potential new promoters or markers for other annotation which are currently undiscovered...
  8. doi request reprint Analyzing ChIP-seq data: preprocessing, normalization, differential identification, and binding pattern characterization
    Cenny Taslim
    Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH, USA
    Methods Mol Biol 802:275-91. 2012
    ..In addition, we provide a sample analysis of ChIP-seq data using the steps provided in the guideline...
  9. pmc Comparisons of methods for linkage analysis and haplotype reconstruction using extended pedigree data
    Shili Lin
    Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA
    BMC Genet 6:S76. 2005
    ..For this study, we had knowledge of the simulating models at the time we performed the analysis...
  10. pmc Breast cancer-associated fibroblasts confer AKT1-mediated epigenetic silencing of Cystatin M in epithelial cells
    Huey Jen L Lin
    Division of Medical Technology, School of Allied Medical Professions, Human Cancer Genetics Program, The Ohio State University, Columbus, Ohio 43210, USA
    Cancer Res 68:10257-66. 2008
    ..Because this two-way interaction is anticipated, the described coculture system can be used to determine the effect of epithelial factors on fibroblasts in future studies...
  11. pmc Heritable clustering and pathway discovery in breast cancer integrating epigenetic and phenotypic data
    Zailong Wang
    Mathematical Biosciences Institute, The Ohio State University, 231 W, 18th Avenue, Columbus, OH 43210, USA
    BMC Bioinformatics 8:38. 2007
    ..Furthermore, our likelihood-based clustering algorithm has great flexibility, allowing for incomplete epigenotype or clinical phenotype data and also permitting dependencies among variables...
  12. ncbi request reprint Evaluations of maximization procedures for estimating linkage parameters under heterogeneity
    Swati Biswas
    Department of Statistics, Ohio State University, Columbus, Ohio 43210, USA
    Genet Epidemiol 26:206-17. 2004
    ..We also show how to obtain standard errors (SEs) for EM and SEM estimates, using methods available in the literature. These SEs can then be combined with the corresponding estimates to provide confidence intervals of the parameters...
  13. pmc DIME: R-package for identifying differential ChIP-seq based on an ensemble of mixture models
    Cenny Taslim
    Department of Molecular Virology, Immunology and Medical Genetics and Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
    Bioinformatics 27:1569-70. 2011
    ..Availability and implementation: DIME is implemented as an R-package, which is available at http://www.stat.osu.edu/~statgen/SOFTWARE/DIME. It may also be downloaded from http://cran.r-project.org/web/packages/DIME/...
  14. pmc Interval estimation of disease loci: development and applications of new linkage methods
    Charalampos Papachristou
    Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA
    BMC Genet 6:S21. 2005
    ..For our analysis with the simulated data, we had knowledge of the simulating models at the time we performed the analysis...
  15. pmc On modeling locus heterogeneity using mixture distributions
    Shili Lin
    Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
    BMC Genet 5:29. 2004
    ..This parameter is usually interpreted as the overall proportion of linked families...
  16. ncbi request reprint A confidence set inference procedure for gene mapping using markers with incomplete polymorphism
    Charalampos Papachristou
    Department of Statistics, Ohio State University, Columbus, Ohio, USA
    Hum Hered 59:1-13. 2005
    ..Application of CSI to the data provided by the Genetic Analysis Workshop 13 yields encouraging results, as they compare favorably to those obtained from GENEHUNTER using its NPL sib-pair method...
  17. pmc Generalized linear modeling with regularization for detecting common disease rare haplotype association
    Wei Guo
    Department of Statistics, The Ohio State University, Columbus, Ohio 43210 1247, USA
    Genet Epidemiol 33:308-16. 2009
    ..Furthermore, our results indicate that rGLM can uncover the associated variants much more frequently than can hapassoc...
  18. pmc Monte Carlo pedigree disequilibrium test for markers on the X chromosome
    Jie Ding
    Department of Statistics, The Ohio State University, Columbus, OH 43210 1247, USA
    Am J Hum Genet 79:567-73. 2006
    ..This set of methods was compared with existing approaches through simulation, and substantial power gains were observed in all settings considered, with type I error rates closely tracking their nominal values...
  19. doi request reprint Space oriented rank-based data integration
    Shili Lin
    The Ohio State University, USA
    Stat Appl Genet Mol Biol 9:Article20. 2010
    ....
  20. ncbi request reprint A two-step procedure for constructing confidence intervals of trait loci with application to a rheumatoid arthritis dataset
    Charalampos Papachristou
    Department of Statistics, Ohio State University, Columbus, 43210, USA
    Genet Epidemiol 30:18-29. 2006
    ..The method not only successfully localized a well-characterized trait contributing locus on chromosome 6, but also placed its position to narrower regions when compared to their LOD support interval counterparts based on the same data...
  21. pmc A quantitative proteomic workflow for characterization of frozen clinical biopsies: laser capture microdissection coupled with label-free mass spectrometry
    John P Shapiro
    Department of Molecular Virology, Immunology and Medical Genetics, College of Medicine, Columbus, OH 43210, USA
    J Proteomics 77:433-40. 2012
    ..These examples illustrate that tissue proteomics carried out on limited clinical material can obtain informative proteomic signatures for disease pathogenesis and demonstrate the suitability of this approach for biomarker discovery...
  22. pmc Integrated analysis identifies a class of androgen-responsive genes regulated by short combinatorial long-range mechanism facilitated by CTCF
    Cenny Taslim
    Department of Statistics, The Ohio State University, Columbus, OH 43210, USA
    Nucleic Acids Res 40:4754-64. 2012
    ..Under such a mechanism, H3K4me2, AR and FoxA1 within the same CTCF block combinatorially regulate a subset of distally located androgen-responsive genes involved in prostate carcinogenesis...
  23. doi request reprint Likelihood approach for detecting imprinting and in utero maternal effects using general pedigrees from prospective family-based association studies
    Jingyuan Yang
    Department of Statistics, The Ohio State University, 404 Cockins Hall, 1958 Neil Avenue, Columbus, Ohio 43210, USA
    Biometrics 68:477-85. 2012
    ....
  24. pmc Comparative study on ChIP-seq data: normalization and binding pattern characterization
    Cenny Taslim
    Department of Molecular Virology, Immunology and Medical Genetics, Ohio State University, Columbus, OH 43210, USA
    Bioinformatics 25:2334-40. 2009
    ..Here, we present a non-linear normalization algorithm and a mixture modeling method for comparing ChIP-seq data from multiple samples and characterizing genes based on their RNA polymerase II (Pol II) binding patterns...
  25. pmc Methylation analysis by microarray
    Daniel E Deatherage
    Human Cancer Genetics Program, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
    Methods Mol Biol 556:117-39. 2009
    ..Issues regarding quality control are addressed as well...
  26. ncbi request reprint Mixture modeling of progression pathways of heterogeneous breast tumors
    Shili Lin
    Department of Statistics and Mathematical Biosciences Institute, The Ohio State University, Columbus, OH 43210, USA
    J Theor Biol 249:254-61. 2007
    ..In particular, for data graded under the Van Nuys system, the mixture model was shown to be consistent with the observed data at the 1% significant level...
  27. ncbi request reprint Class discovery and classification of tumor samples using mixture modeling of gene expression data--a unified approach
    Roxana Alexandridis
    Department of Statistics, Ohio State University, 1958 Neil Avenue, Columbus, OH 43210, USA
    Bioinformatics 20:2545-52. 2004
    ..Further evaluation of the method was carried out on other variants of the leukemia data and a colon dataset...
  28. ncbi request reprint Microarray analysis of gene expression: considerations in data mining and statistical treatment
    Joseph S Verducci
    Davis Heart and Lung Research Institute, Department of Surgery, The Ohio State University, Columbus, Ohio, USA
    Physiol Genomics 25:355-63. 2006
    ....
  29. pmc Gamma-Normal-Gamma mixture model for detecting differentially methylated loci in three breast cancer cell lines
    Abbas Khalili
    Department of Statistics, The Ohio State University, Columbus, OH 43210 1247, USA
    Cancer Inform 3:43-54. 2007
    ..Although the GNG model was proposed in the context of single-slide methylation analysis, it can be readily adapted to analyze multi-slide methylation data as well as other types of microarray data...
  30. ncbi request reprint MicroRNA expression profiles for the NCI-60 cancer cell panel
    Paul E Blower
    Program of Pharmacogenomics, Department of Pharmacology and the Comprehensive Cancer Center, College of Medicine, The Ohio State University, 5072 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210, USA
    Mol Cancer Ther 6:1483-91. 2007
    ..Combined with gene expression and other biological data using multivariate analysis, microRNA expression profiles may provide a critical link for understanding mechanisms involved in chemosensitivity and chemoresistance...
  31. ncbi request reprint Linkage analysis with sequential imputation
    Zachary Skrivanek
    Department of Statistics, Ohio State University, Columbus, Ohio 43210, USA
    Genet Epidemiol 25:25-35. 2003
    ..The power gains of using all pedigree members were substantial under 2 of the 3 models. We implemented sequential imputation for multilocus linkage analysis in a user-friendly software package called SIMPLE...
  32. ncbi request reprint Information gain for genetic parameter estimation with incorporation of marker data
    Yuqun Luo
    Center for Biostatistics, Ohio State University 1958 Neil Avenue, Columbus, Ohio 43210, USA
    Biometrics 59:393-401. 2003
    ..Incorporation of marker data in larger pedigrees also yields greater information gains based on both criteria. The effect of pedigree structure is also studied...
  33. pmc CD24 is a genetic modifier for risk and progression of multiple sclerosis
    Qunmin Zhou
    Division of Cancer Immunology and Department of Pathology, Ohio State University, Columbus, OH 43210, USA
    Proc Natl Acad Sci U S A 100:15041-6. 2003
    ..Thus, CD24 polymorphism is a genetic modifier for susceptibility and progression of MS in the central Ohio cohort that we studied, perhaps by affecting the efficiency of CD24 expression on the cell surface...
  34. doi request reprint An optimum projection and noise reduction approach for detecting rare and common variants associated with complex diseases
    Asuman Turkmen
    Department of Statistics, The Ohio State University, Columbus, Ohio 43055, USA
    Hum Hered 74:51-60. 2012
    ..Consequently, there is currently a great deal of interest in developing methods that can interrogate rare variants for association with diseases...
  35. pmc Multilocus LD measure and tagging SNP selection with generalized mutual information
    Zhenqiu Liu
    Department of Statistics, Ohio State University, Columbus, Ohio 43210 1247, USA
    Genet Epidemiol 29:353-64. 2005
    ..The results indicate that multilocus LD patterns can be captured well, and informative and nonredundant SNPs can be selected effectively from a large set of loci...
  36. ncbi request reprint Serial analysis of gene expression profiles of adult and aged mouse cerebellum
    Magdalena C Popesco
    Department of Pharmacology, The Ohio State University, Columbus, OH 43210, USA
    Neurobiol Aging 29:774-88. 2008
    ....
  37. doi request reprint Logistic Bayesian LASSO for identifying association with rare haplotypes and application to age-related macular degeneration
    Swati Biswas
    Department of Biostatistics, School of Public Health, University of North Texas Health Science Center, Fort Worth, Texas 76107, USA
    Biometrics 68:587-97. 2012
    ..Our results show that LBL is much more powerful in identifying rare associated haplotypes when the false positive rates for both approaches are kept the same...
  38. pmc ADAMTS13 activity and antigen during therapy and follow-up of patients with idiopathic thrombotic thrombocytopenic purpura: correlation with clinical outcome
    Shangbin Yang
    Department of Pathology, College of Medicine, Ohio State University, Columbus, OH 43210, USA
    Haematologica 96:1521-7. 2011
    ..The assay for ADAMTS13 activity helps clinicians to confirm the clinical diagnosis of idiopathic thrombotic thrombocytopenic purpura. The clinical value of testing for the antigen level of ADAMTS13 protein is, however, less clear...
  39. pmc Linkage analysis of the simulated data - evaluations and comparisons of methods
    Swati Biswas
    Department of Statistics, The Ohio State University, 1958 Neil Avenue, Columbus, Ohio, USA
    BMC Genet 4:S70. 2003
    ..In contrast to the standard methods, most of the new approaches are able to identify at least one of the disease genes in all the replicates considered...
  40. ncbi request reprint Finding starting points for Markov chain Monte Carlo analysis of genetic data from large and complex pedigrees
    Yuqun Luo
    Center for Biostatistics, The Ohio State University, Columbus, 43210, USA
    Genet Epidemiol 25:14-24. 2003
    ..The algorithm has been applied to both simulated and real data on two large and complex Hutterite pedigrees under many settings, and good results are obtained. The algorithm has been implemented in a user-friendly package called START...
  41. doi request reprint Demographic and ADAMTS13 biomarker data as predictors of early recurrences of idiopathic thrombotic thrombocytopenic purpura
    Spero R Cataland
    Department of Medicine, Columbus, OH, USA
    Eur J Haematol 83:559-64. 2009
    ..We studied the clinical utility of demographic and ADAMTS13 biomarker data to predict the risk for exacerbation...
  42. pmc Photoperiod reverses the effects of estrogens on male aggression via genomic and nongenomic pathways
    Brian C Trainor
    Department of Psychology, Institute for Behavioral Medicine Research, Ohio State University, Columbus, OH 43210, USA
    Proc Natl Acad Sci U S A 104:9840-5. 2007
    ..These data demonstrate that the environment can dictate how hormones affect a complex behavior by altering the molecular pathways targeted by steroid receptors...
  43. pmc Haplotype association analysis of North American Rheumatoid Arthritis Consortium data using a generalized linear model with regularization
    Wei Guo
    Department of Statistics, The Ohio State University, Columbus, Ohio 43210 USA
    BMC Proc 3:S32. 2009
    ..A total of 444 and 43 four-SNP tests were found to be significant at the Bonferroni corrected 5% significance level on chromosome 6 and 18, respectively...