Keles Research Group

Group members are indicated in bold.

Our research is supported by an RO1 grant from NIH/NHGRI, an NSF DMS grant (# 0804597) and a research starter award from the PhRMA Foundation.

2008

• K. H. Eng, H. Corrado Bravo, G. Wahba, S. Keles (2008). A phylogenetic mixture model for the evolution of gene expression. Submitted.

• K. H. Eng, S. Keles, G. Wahba (2008). A linear mixed effects clustering model for multi-species time course gene expression data. Submitted. Supplementary Materials.

• H. Corrada Bravo, K. H. Eng, S. Keles, G. Wahba, S. Wright (2008). Estimating tree-structured covariance matrices via mixed-integer programming with an application to phylogenetic analysis of gene expression. Submitted.

• H. Chun and S. Keles (2008). Expression quantitative trait loci mapping with multivariate sparse partial least squares regression. Submitted.

• P-F. Kuan, D. Huebert, A. Gasch, S. Keles (2008) . A Non-homogeneous hidden Markov model on first order differences for automatic detection of nucleosome positions. Submitted. Supplementary materials.

• H. Wei*, P-F. Kuan*, S. Tian, C. Yang, J. Nie, S. Sengupta, V. Ruotti, G. Jonsdottir, S. Keles, J. A. Thomson, R. Stewart (2008). A study of the relationships between oligonucleotide properties and hybridization intensities from Nimblegen microarray dataset. Nucleic Acids Research, 36(9):2926-2938. *: Joint first authors.

• S. Keles, C. L. Warren, C. D. Carlson, A. Z. Ansari (2008) CSI-Tree: A regression tree approach for modeling binding properties of DNA binding molecules based on cognate site identification (CSI) data. Nucleic Acids Research, 36(10): 3171-3184. Supplementary materials.

• R. Jornsten and S. Keles (2008). Mixture models with multiple levels, with application to the analysis of multi-factor gene expression data. Biostatistics, Feb 5. [Journal website]

2007

• S. Keles and H. Chun (2007). Comments on: “Augmenting the bootstrap to analyze high dimensional genomic
  data”, Connections to the ridge regularized covariance estimator with bagging. Invited discussion paper by S. Tyekucheva and F. Chiarmonte. TEST, 17 (1): 36-39. Supplementary materials.

• H. Chun and S. Keles (Nov 2007). Sparse partial least squares for simultaneous dimension reduction and variable selection. Submitted.

• Y. Isogai, S. Keles, M. Prestel, A. Hochheimer, and R. Tjian (2007). Transcription of histone gene cluster by differential core-promoter factors. Genes and Development, 21: 2936-2949.

• L.A. Goff, J. Davila, R. Jornsten, S. Keles, and R.P. Hart (2007) Bioinformatic Analysis of Neural Stem Cell Differentiation. Journal of Biomolecular Techniques, 18: 205-212.

• P-F. Kuan, H. Chun, and S. Keles (2008). CMARRT: A tool for the analysis of ChIP-chip data from tiling arrays by incorporating the correlation structure. Proceedings of the Pacific Symposium of Biocomputing, 13: 515-526. [2nd poster prize in the 1st Midwest Symposium of Computational Biology and Bioinformatics.] Supplementary materials. CMARRT SOFTWARE.

• S. Dudoit, S. Keles, M. J. van der Laan (2007). Multiple tests of association with biological annotation metadata. In D. Nolan and T. P. Speed (eds), Probability and Statistics: Essays in Honor of David A. Freedman, Vol. 2 of IMS Collections, p. 153-218.

• D. R. Hopkins, S. Keles, D. S. Greenspan (2007). The bone morphogenetic protein 1/Tolloid-like metalloproteinases. Matrix Biology, 26(7): 508-23.

• N. K. Sweitzer, T. LeCaire, J. H. Stein, S. Keles, M. Palta, G. F. Mitchell (2007). Increases in central aortic impedance precede alterations in arterial stiffness measures in type 1 Diabetes Mellitus. Diabetes Care, 30:2886-2891.

• H. Shim and S. Keles (2007). Integrating quantitative information from ChIP-chip experiments into motif finding. Biostatistics, 9(1):51-65. Supplementary materials. [Software coming soon - will be an extended module for cosmo]

• K. H. Eng, D. Kvitek, G.Wahba, A. Gasch, and S. Keles (2007). Exploratory statistical analysis of multi-species time course gene expression data. Proceedings of the 56th Session of the International Statistical Institute. Invited Paper.
  

• Y. Isogai, S. Takada, R. Tjian, S. Keles, (2007). Novel TRF1/BRF target genes revealed by genome-wide analysis of Drosophila Pol III transcription. The EMBO Journal, 26(1): 79–89.

• S. Keles (2007). Mixture modeling for genome-wide localization of transcription factors. Biometrics, 63(1): 10-21. [Recipient of the David Byar Young Investigator Award for 2006] [TileHGMM R package] [TileHGMM Vignette]

• O. Bembom, S. Keles, and M. J. van der Laan (2007). Supervised detection of conserved motifs in DNA sequences with cosmo. Statistical Applications in Genetics and Molecular Biology, Volume 6: Issue 1, Article 8. [cosmo software]

2006

• S. Keles, M. J. van der Laan, Sandrine Dudoit, and Simon E. Cawley (2006). Multiple testing methods for ChIP-Chip high density oligonucleotide array data. Journal of Computational Biology. 13(3): 579-613.

2005

• F. Lu, S. Keles, S. Wright, and Wahba, G. (2005) A Framework for kernel regularization with application to protein clustering. PNAS, 102 (35): 12332-12337.

• H. Cinar, S. Keles, and Y. Jin (2005). Expression profiling of GABAergic motor neurons in Caenorhabditis elegans. Current Biology, 15 (4): 340 -346. (Journal website)

2004

• S. Keles, M.J. van der Laan, and S. Dudoit (2004). Asymptotically optimal model selection method for regression on censored outcomes. Bernoulli, 10 (6): 1011-1037.

• S. Keles, M. J. van der Laan, and C. Vulpe (2004). Regulatory motif finding using logic regression. Bioinformatics, 20 (16): 2799-2811. (Journal website) [mfure R package]

• M. J. van der Laan, S. Dudoit, and S. Keles(2004). Asymptotic optimality of likelihood-based cross-validation. Statistical Applications in Genetics and Molecular Biology, Vol. 3, No. 1, Article 3. (Journal website)

• J. De Freitas, J. Kim, H. Poynton, T. Su, H. Wintz, T. Fox, P. Holman, A. Loguinov, S. Keles, M.J. van der Laan, and C. Vulpe (2004). Exploratory and confirmatory gene expression profiling of mac1. Journal of Biological Chemistry, 2 (6): 4450-4458.

• M. Miloslavsky, S.Keles, M.J. van der Laan, and S. Butler (2004).Recurrent events analysis in the presence of time dependent covariates and dependent censoring. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66 (1): 239-257.

• S. Keles, M.J. van der Laan, and J.M. Robins (2004).Estimation of the bivariate survival function with right censored data structures. Handbook of Statistics, Volume 23: Advances in Survival Analysis, edited by N. Balakrishnan and C.R. Rao.

2003

• S. Dudoit, M. J. van der Laan, S. Keles, A. M. Molinaro, S. E. Sinisi, and S. L. Teng (2003). Loss-Based Estimation with Cross-Validation: Applications to Microarray Data Analysis and Motif Finding. SIGKDD Explotaions, 5 (2): 37-49.

• S. Keles, M.J. van der Laan, S. Dudoit, B. Xing, and M.B. Eisen (2003). Supervised detection of regulatory motifs in DNA sequences. Statistical Applications in Genetics and Molecular Biology, Vol. 2, No. 1, Article 5.(Journal website)

2002

• S. Keles, M.J. van der Laan, and M. B. Eisen (2002). Identification of regulatory elements using a feature selection method. Bioinformatics, 18: 1167-1175. (Journal website)

• S. Keles, M.R. Segal (2002). Residual-based tree-structured survival analysis. Statistics in Medicine, 21: 313-326. (Journal website)

Dissertation

• S. Keles (2003). Statistical methods for cis-regulatory motif detection in DNA sequences and Two censored data problems, Ph.D. dissertation