Sunduz Keles

Personal Details

First Name:	Sunduz
Middle Name:
Last Name:	Keles
Suffix:
RePEc Short-ID:	pke65
	[This author has chosen not to make the email address public]
	http://www.stat.wisc.edu/~keles

Affiliation

University of Wisconsin, Madison, Department of Statistics

http://www.stat.wisc.edu
Madison, WI

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Sunduz Keles & Mark van der Laan & Chris Vulpe, 2004. "Regulatory Motif Finding by Logic Regression," U.C. Berkeley Division of Biostatistics Working Paper Series 1145, Berkeley Electronic Press.

   Cited by:

   1. Baierl, Andreas & Futschik, Andreas & Bogdan, Malgorzata & Biecek, Przemyslaw, 2007. "Locating multiple interacting quantitative trait loci using robust model selection," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6423-6434, August.
   2. Insuk Sohn & Jooyong Shim & Changha Hwang & Sujong Kim & Jae Won Lee, 2014. "Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 573-581, March.
   3. Sohn, Insuk & Shim, Jooyong & Hwang, Changha & Kim, Sujong & Lee, Jae Won, 2009. "Informative transcription factor selection using support vector machine-based generalized approximate cross validation criteria," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1727-1735, March.
   4. Yuan Yuan & Lei Guo & Lei Shen & Jun S Liu, 2007. "Predicting Gene Expression from Sequence: A Reexamination," PLOS Computational Biology, Public Library of Science, vol. 3(11), pages 1-7, November.
   5. Tuglus Catherine & van der Laan Mark J., 2011. "Repeated Measures Semiparametric Regression Using Targeted Maximum Likelihood Methodology with Application to Transcription Factor Activity Discovery," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-31, January.
   6. Siewert Elizabeth A & Kechris Katerina J, 2009. "Prediction of Motifs Based on a Repeated-Measures Model for Integrating Cross-Species Sequence and Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-36, September.

2. Sandrine Dudoit & Mark van der Laan & Sunduz Keles & Annette Molinaro & Sandra Sinisi & Siew Leng Teng, 2004. "Loss-Based Estimation with Cross-Validation: Applications to Microarray Data Analysis and Motif Finding," U.C. Berkeley Division of Biostatistics Working Paper Series 1136, Berkeley Electronic Press.

   Cited by:

   1. Laan Mark J. van der & Dudoit Sandrine & Vaart Aad W. van der, 2006. "The cross-validated adaptive epsilon-net estimator," Statistics & Risk Modeling, De Gruyter, vol. 24(3), pages 373-395, December.
   2. Molinaro, Annette M. & Dudoit, Sandrine & van der Laan, M.J.Mark J., 2004. "Tree-based multivariate regression and density estimation with right-censored data," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 154-177, July.
   3. Olivier Lopez & Xavier Milhaud & Pierre-Emmanuel Thérond, 2016. "Tree-based censored regression with applications in insurance," Post-Print hal-01141228, HAL.

3. Sunduz Keles & Mark van der Laan & Sandrine Dudoit & Simon Cawley, 2004. "Multiple Testing Methods For ChIP-Chip High Density Oligonucleotide Array Data," U.C. Berkeley Division of Biostatistics Working Paper Series 1147, Berkeley Electronic Press.

   Cited by:

   1. Bérard Caroline & Martin-Magniette Marie-Laure & Brunaud Véronique & Aubourg Sébastien & Robin Stéphane, 2011. "Unsupervised Classification for Tiling Arrays: ChIP-chip and Transcriptome," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-22, November.
   2. Raphael Gottardo & Wei Li & W. Evan Johnson & X. Shirley Liu, 2008. "A Flexible and Powerful Bayesian Hierarchical Model for ChIP–Chip Experiments," Biometrics, The International Biometric Society, vol. 64(2), pages 468-478, June.
   3. Olbricht Gayla R. & Craig Bruce A. & Doerge Rebecca W., 2012. "Incorporating Genomic Annotation into a Hidden Markov Model for DNA Methylation Tiling Array Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(5), pages 1-37, November.
   4. Hongkai Ji & Wing Hung Wong, 2006. "Computational Biology: Toward Deciphering Gene Regulatory Information in Mammalian Genomes," Biometrics, The International Biometric Society, vol. 62(3), pages 645-663, September.
   5. Anat Reiner-Benaim, 2016. "Scan Statistic Tail Probability Assessment Based on Process Covariance and Window Size," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 717-745, September.
   6. Jonathan A. L. Gelfond & Mayetri Gupta & Joseph G. Ibrahim, 2009. "A Bayesian Hidden Markov Model for Motif Discovery Through Joint Modeling of Genomic Sequence and ChIP-Chip Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1087-1095, December.

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