Sunduz Keles is Associate Professor of Statistics and of Biostatistics and Medical Informatics at the University of Wisconsin, Madison. Professor Keles's research interests broadly include statistical genomics with specific focus on: Design and analysis of tiling array and high throughput sequencing experiments. Sequence analysis. Comparative genomics. Statistical models for the evolution of gene expression. Genomic data integration. Dimension reduction and variable selection with applications to genomics.
Microarrays
Regulatory Motif Finding by Logic Regression (with Mark J. van der Laan and Chris Vulpe), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)
Multiple transcription factors coordinately control transcriptional regulation of genes in eukaryotes. Although multiple computational methods...
Survival Analysis
Asymptotically Optimal Model Selection Method with Right Censored Outcomes (with Mark J. van der Laan and Sandrine Dudoit), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)
Over the last two decades, non-parametric and semi-parametric approaches that adapt well known techniques such...
Recurrent Events Analysis in the Presence of Time Dependent Covariates and Dependent Censoring (with Maja Miloslavsky, Mark J. van der Laan, and Steve Butler), U.C. Berkeley Division of Biostatistics Working Paper Series (2002)
Recurrent events models have lately received a lot of attention in the literature. The majority...
Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures (with Mark J. van der Laan and James M. Robins), U.C. Berkeley Division of Biostatistics Working Paper Series (2002)
We propose a bivariate survival function estimator for a general right censored data structure that...
Computational Biology
Supervised detection of conserved motifs in DNA sequences with cosmo (with Oliver Bembom and Mark J. van der Laan), Statistical Applications in Genetics and Molecular Biology (2007)
A number of computational methods have been proposed for identifying transcription factor binding sites from...
Supervised Detection of Conserved Motifs in DNA Sequences with cosmo (with Oliver Bembom and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2006)
A number of computational methods have been proposed for identifying transcription factor binding sites from...
Multiple Tests of Association with Biological Annotation Metadata (with Sandrine Dudoit and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2006)
We propose a general and formal statistical framework for the multiple tests of associations between...
Regulatory Motif Finding by Logic Regression (with Mark J. van der Laan and Chris Vulpe), U.C. Berkeley Division of Biostatistics Working Paper Series (2004)
Multiple transcription factors coordinately control transcriptional regulation of genes in eukaryotes. Although multiple computational methods...
Identification of Regulatory Elements Using A Feature Selection Method (with Mark J. van der Laan and Michael B. Eisen), U.C. Berkeley Division of Biostatistics Working Paper Series (2001)
Many methods have been described to identify regulatory motifs in the transcription control regions of...
Software
cosmoweb: A web application for the supervised detection of conserved motifs in DNA sequences. (with Oliver Bembom and Mark Johannes van der Laan), Oliver Bembom (2006)
cosmo searches a set of unaligned DNA sequences for a shared motif that may, for...
ccosmo: A stand-along C program for the supervised detection of conserved motifs in DNA sequences. (with Oliver Bembom and Mark Johannes van der Laan), Oliver Bembom (2006)
cosmo searches a set of unaligned DNA sequences for a shared motif that may, for...
Statistical Models
Supervised Detection of Regulatory Motifs in DNA Sequences (with Mark J. van der Laan, Sandrine Dudoit, Biao Xing, and Michael B. Eisen ), Statistical Applications in Genetics and Molecular Biology (2010)
Identification of transcription factor binding sites (regulatory motifs) is a major interest in contemporary biology....
A Non-Homogeneous Hidden-State Model on First Order Differences for Automatic Detection of Nucleosome Positions (with Pei Fen Kuan, Dana Huebert, and Audrey Gasch), Statistical Applications in Genetics and Molecular Biology (2010)
The ability to map individual nucleosomes accurately across genomes enables the study of relationships between...
Supervised Detection of Conserved Motifs in DNA Sequences with Cosmo (with Oliver Bembom and Mark J. van der Laan), Statistical Applications in Genetics and Molecular Biology (2010)
A number of computational methods have been proposed for identifying transcription factor binding sites from...
A Statistical Framework for the Analysis of ChIP-Seq Data (with Pei Fen Kuan, Dongjun Chung, Guangjin Pan, James A. Thomson, and Ron Stewart), Journal of the American Statistical Association (2009)
Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins,...
Multiple Tests of Association with Biological Annotation Metadata (with Sandrine Dudoit and Mark J. van der Laan), U.C. Berkeley Division of Biostatistics Working Paper Series (2006)
We propose a general and formal statistical framework for the multiple tests of associations between...
Statistical Theory and Methods
Asymptotic Optimality of Likelihood-Based Cross-Validation (with Mark J. van der Laan and Sandrine Dudoit), Statistical Applications in Genetics and Molecular Biology (2010)
Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d....
Asymptotically Optimal Model Selection Method with Right Censored Outcomes (with Mark J. van der Laan and Sandrine Dudoit), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)
Over the last two decades, non-parametric and semi-parametric approaches that adapt well known techniques such...
Asymptotic Optimality of Likelihood Based Cross-Validation (with Mark J. van der Laan and Sandrine Dudoit), U.C. Berkeley Division of Biostatistics Working Paper Series (2003)
Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d....
Recurrent Events Analysis in the Presence of Time Dependent Covariates and Dependent Censoring (with Maja Miloslavsky, Mark J. van der Laan, and Steve Butler), U.C. Berkeley Division of Biostatistics Working Paper Series (2002)
Recurrent events models have lately received a lot of attention in the literature. The majority...
Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures (with Mark J. van der Laan and James M. Robins), U.C. Berkeley Division of Biostatistics Working Paper Series (2002)
We propose a bivariate survival function estimator for a general right censored data structure that...
Computational Biology/Bioinformatics
Supervised Detection of Regulatory Motifs in DNA Sequences (with Mark J. van der Laan, Sandrine Dudoit, Biao Xing, and Michael B. Eisen ), Statistical Applications in Genetics and Molecular Biology (2010)
Identification of transcription factor binding sites (regulatory motifs) is a major interest in contemporary biology....
A Non-Homogeneous Hidden-State Model on First Order Differences for Automatic Detection of Nucleosome Positions (with Pei Fen Kuan, Dana Huebert, and Audrey Gasch), Statistical Applications in Genetics and Molecular Biology (2010)
The ability to map individual nucleosomes accurately across genomes enables the study of relationships between...
Supervised Detection of Conserved Motifs in DNA Sequences with Cosmo (with Oliver Bembom and Mark J. van der Laan), Statistical Applications in Genetics and Molecular Biology (2010)
A number of computational methods have been proposed for identifying transcription factor binding sites from...
A Statistical Framework for the Analysis of ChIP-Seq Data (with Pei Fen Kuan, Dongjun Chung, Guangjin Pan, James A. Thomson, and Ron Stewart), Journal of the American Statistical Association (2009)
Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins,...
Multiple Testing Methods For ChIP–Chip High Density Oligonucleotide Array Data (with Mark J. van der Laan, Sandrine Dudoit, and Simon E. Cawley), Journal of Computational Biology (2006)
Cawley et al. (2004) have recently mapped the locations of binding sites for three transcription...