Sündüz Keleş

FreeHi-C Spike-in Simulations for Benchmarking Differential Chromatin Interaction Detection.

Ye Zheng, Peigen Zhou, Sündüz Keleş, 2020, Methods.

Statistical analysis of ChIP-seq data with MOSAiCS.

Sündüz Keleş, Dongjun Chung, Guannan Sun, 2013, Methods in molecular biology.

Annotation Regression for Genome-Wide Association Studies with an Application to Psychiatric Genomic Consortium Data

Sündüz Keleş, Sunyoung Shin, S. Keleş, 2016, Statistics in Biosciences.

A Statistical Framework for the Analysis of ChIP-Seq Data

Sündüz Keleş, Ron Stewart, Pei Fen Kuan, 2011, Journal of the American Statistical Association.

Mixture models with multiple levels, with application to the analysis of multifactor gene expression data.

Rebecka Jörnsten, Sündüz Keleş, S. Keleş, 2008, Biostatistics.

Mixture Modeling for Genome‐Wide Localization of Transcription Factors

Sündüz Keleş, S. Keleş, 2007, Biometrics.

A Hierarchical Framework for State-Space Matrix Inference and Clustering.

Chandler Zuo, Sündüz Keleş, Emery H Bresnick, 2015, The annals of applied statistics.

dPeak: High Resolution Identification of Transcription Factor Binding Sites from PET and SET ChIP-Seq Data

Sündüz Keleş, Dongjun Chung, Kevin S. Myers, 2013, PLoS Comput. Biol..

FreeHi-C simulates high fidelity Hi-C data for benchmarking and data augmentation

Ye Zheng, Sündüz Keleş, S. Keleş, 2019, Nature Methods.