A Gibbs Sampler for the Detection of Subtle Motifs in Multiple Sequences. - Charles E. Lawrence; Stephen F. Altschul; John C. Wootton; Mark S. Boguski; Andrew F. Neuwald; Jun S. Liu (HICSS (5), 1994)

Metropolized independent sampling with comparisons to rejection sampling and importance sampling. - Jun S. Liu (Stat. Comput., 1996)

Bayesian Adaptive Alignment and Inference. - Jun Zhu; Jun S. Liu; Charles E. Lawrence (ISMB, 1997)

Bayesian adaptive sequence alignment algorithms. - Jun Zhu; Jun S. Liu; Charles E. Lawrence (Bioinform., 1998)

Relaxed Simulated Tempering for VLSI Floorplan Designs. - Jason Cong; Tianming Kong; Dongmin Xu; Faming Liang; Jun S. Liu; Wing Hung Wong (ASP-DAC, 1999)

Bayesian inference on biopolymer models. - Jun S. Liu; Charles E. Lawrence (Bioinform., 1999)

Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application. - Jason Cong; Tianming Kong; Faming Liang; Jun S. Liu; Wing Hung Wong; Dongmin Xu (ASP-DAC, 2000)

Bayesian Segmentation of Protein Secondary Structure. - Scott C. Schmidler; Jun S. Liu; Douglas L. Brutlag (J. Comput. Biol., 2000)

Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering. - Rong Chen; Xiaodong Wang; Jun S. Liu (IEEE Trans. Inf. Theory, 2000)

A Theoretical Framework for Sequential Importance Sampling with Resampling. - Jun S. Liu; Rong Chen; Tanya Logvinenko (Sequential Monte Carlo Methods in Practice, 2001)

BioProspector: Discovering Conserved DNA Motifs in Upstream Regulatory Regions of Co-Expressed Genes. - X. Liu; Douglas L. Brutlag; Jun S. Liu (Pacific Symposium on Biocomputing, 2001)

Haplotype Inference and Its Application in Linkage Disequilibrium Mapping. - Tianhua Niu; Xin Lu; Hosung Kang; Zhaohui S. Qin; Jun S. Liu (Computational Methods for SNPs and Haplotype Inference, 2002)

Dynamic Programming Algorithms for Haplotype Block Partitioning and Tag SNP Selection Using Haplotype Data or Genotype Data. - Kui Zhang; Ting Chen 006; Michael S. Waterman; Zhaohui S. Qin; Jun S. Liu; Fengzhu Sun (Computational Methods for SNPs and Haplotype Inference, 2002)

Convergence analyses and comparisons of Markov chain Monte Carlo algorithms in digital communications. - Rong Chen; Jun S. Liu; Xiaodong Wang (IEEE Trans. Signal Process., 2002)

Monte Carlo Bayesian Signal Processing for Wireless Communications. - Xiaodong Wang; Rong Chen; Jun S. Liu (J. VLSI Signal Process., 2002)

BPPS: An Algorithm for Analyzing Protein Sequence Alignments. - Jun S. Liu (CSB, 2003)

Statistical Resynchronization and Detection of Periodic Transcripts. - Xin Lu; Wen Zhang; Zhaohui S. Qin; Jun S. Liu (CSB, 2003)

BioOptimizer: a Bayesian scoring function approach to motif discovery. - Shane T. Jensen; Jun S. Liu (Bioinform., 2004)

Modeling within-motif dependence for transcription factor binding site predictions. - Qing Zhou; Jun S. Liu (Bioinform., 2004)

Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model. - Andrew F. Neuwald; Jun S. Liu (BMC Bioinform., 2004)

Determination of Local Statistical Significance of Patterns in Markov Sequences with Application to Promoter Element Identification. - Haiyan Huang; Ming-Chih J. Kao; Xianghong Jasmine Zhou; Jun S. Liu; Wing Hung Wong (J. Comput. Biol., 2004)

A suite of web-based programs to search for transcriptional regulatory motifs. - Yueyi Liu; Liping Wei; Serafim Batzoglou; Douglas L. Brutlag; Jun S. Liu; Xiaole Shirley Liu (Nucleic Acids Res., 2004)

BEST: Binding-site Estimation Suite of Tools. - Dongsheng Che; Shane T. Jensen; Liming Cai; Jun S. Liu (Bioinform., 2005)

A boosting approach for motif modeling using ChIP-chip data. - Pengyu Hong; Xiaole Shirley Liu; Qing Zhou; Xin Lu; Jun S. Liu; Wing Hung Wong (Bioinform., 2005)

Combining phylogenetic motif discovery and motif clustering to predict co-regulated genes. - Shane T. Jensen; Lei Shen; Jun S. Liu (Bioinform., 2005)

HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms. - Kui Zhang; Zhaohui S. Qin; Ting Chen 006; Jun S. Liu; Michael S. Waterman; Fengzhu Sun (Bioinform., 2005)

RSIR: regularized sliced inverse regression for motif discovery. - Wenxuan Zhong; Peng Zeng; Ping Ma 001; Jun S. Liu; Michael Yu Zhu (Bioinform., 2005)

Bayesian models for pooling microarray studies with multiple sources of replications. - Erin M. Conlon; Joon J. Song; Jun S. Liu (BMC Bioinform., 2006)

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. - Xuegong Zhang; Xin Lu; Qian Shi; Xiu-qin Xu; Hon-chiu E. Leung; Lyndsay N. Harris; James D. Iglehart; Alexander Miron; Jun S. Liu; Wing Hung Wong (BMC Bioinform., 2006)

On Side-Chain Conformational Entropy of Proteins. - Jinfeng Zhang; Jun S. Liu (PLoS Comput. Biol., 2006)

Statistial Analysis of nucleosome occupancy and histone modification data. - Guo-Cheng Yuan; Jun S. Liu (BIBE, 2007)

Bayesian Biclustering of Microarray Data. - Jiajun Gu; Jun S. Liu (BIOCOMP, 2007)

Statistical power of phylo-HMM for evolutionarily conserved element detection. - Xiaodan Fan; Jun Zhu; Eric E. Schadt; Jun S. Liu (BMC Bioinform., 2007)

Predicting Gene Expression from Sequence: A Reexamination. - Yuan Yuan; Lei Guo 013; Lei Shen; Jun S. Liu (PLoS Comput. Biol., 2007)

On learning strategies for evolutionary Monte Carlo. - Gopi Goswami; Jun S. Liu (Stat. Comput., 2007)

PFP: A Computational Framework for Phylogenetic Footprinting in Prokaryotic Genomes. - Dongsheng Che; Guojun Li; Shane T. Jensen; Jun S. Liu; Ying Xu 001 (ISBRA, 2008)

Genomic Sequence Is Highly Predictive of Local Nucleosome Depletion. - Guo-Cheng Yuan; Jun S. Liu (PLoS Comput. Biol., 2008)

Systematic Analysis of Pleiotropy in C. elegans Early Embryogenesis. - Lihua Zou; Sira Sriswasdi; Brian C. Ross; Patrycja Vasilyev Missiuro; Jun S. Liu; Hui Ge (PLoS Comput. Biol., 2008)

Bayesian inference of protein-protein interactions from biological literature. - Rajesh Chowdhary; Jinfeng Zhang; Jun S. Liu (Bioinform., 2009)

Information Flow Analysis of Interactome Networks. - Patrycja Vasilyev Missiuro; Kesheng Liu; Lihua Zou; Brian C. Ross; Guoyan Zhao 002; Jun S. Liu; Hui Ge (PLoS Comput. Biol., 2009)

Tmod: toolbox of motif discovery. - Hanchang Sun; Yuan Yuan; Yibo Wu; Hui Liu; Jun S. Liu; Hongwei Xie (Bioinform., 2010)

Genome-wide analysis of regions similar to promoters of histone genes. - Rajesh Chowdhary; Vladimir B. Bajic; Difeng Dong; Limsoon Wong; Jun S. Liu (BMC Syst. Biol., 2010)

A Bayesian Partition Method for Detecting Pleiotropic and Epistatic eQTL Modules. - Wei Zhang; Jun Zhu; Eric E. Schadt; Jun S. Liu (PLoS Comput. Biol., 2010)

Statistical Learning and Modeling of TF-DNA Binding. - Bo Jiang 005; Jun S. Liu (Handbook of Statistical Bioinformatics, 2011)

IMID: integrated molecular interaction database. - Sentil Balaji; Charles Mcclendon; Rajesh Chowdhary; Jun S. Liu; Jinfeng Zhang (Bioinform., 2012)

GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. - Jianxing Feng; Clifford A. Meyer; Qian Wang; Jun S. Liu; Xiaole Shirley Liu; Yong Zhang 006 (Bioinform., 2012)

HiCNorm: removing biases in Hi-C data via Poisson regression. - Ming Hu 001; Ke Deng; Siddarth Selvaraj; Zhaohui S. Qin; Bing Ren; Jun S. Liu (Bioinform., 2012)

Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq. - Ming Hu 001; Yu Zhu; Jeremy M. G. Taylor; Jun S. Liu; Zhaohui S. Qin (Bioinform., 2012)

On Delay Tomography: Fast Algorithms and Spatially Dependent Models. - Ke Deng; Yang Li; Weiping Zhu 001; Zhi Geng; Jun S. Liu (IEEE Trans. Signal Process., 2012)

Bayesian hierarchical model of protein-binding microarray k-mer data reduces noise and identifies transcription factor subclasses and preferred k-mers. - Bo Jiang 005; Jun S. Liu; Martha L. Bulyk (Bioinform., 2013)

PIMiner: a web tool for extraction of protein interactions from biomedical literature. - Rajesh Chowdhary; Jinfeng Zhang; Sin Lam Tan; Daniel E. Osborne; Vladimir B. Bajic; Jun S. Liu (Int. J. Data Min. Bioinform., 2013)

Bayesian Inference of Spatial Organizations of Chromosomes. - Ming Hu 001; Ke Deng; Zhaohui S. Qin; Jesse R. Dixon; Siddarth Selvaraj; Jennifer Fang; Bing Ren; Jun S. Liu (PLoS Comput. Biol., 2013)

Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data. - Ming Hu 001; Ke Deng; Zhaohui S. Qin; Jun S. Liu (Quant. Biol., 2013)

Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms. - Jack Y. Yang; A. Keith Dunker; Jun S. Liu; Xiang Qin; Hamid R. Arabnia; William Yang; Andrzej Niemierko; Zhongxue Chen; Zuojie Luo; Liangjiang Wang; Yunlong Liu; Dong Xu; et al. (BMC Bioinform., 2014)

Identification of genes and pathways involved in kidney renal clear cell carcinoma. - William Yang; Kenji Yoshigoe; Xiang Qin; Jun S. Liu; Jack Y. Yang; Andrzej Niemierko; Youping Deng; Yunlong Liu; A. Keith Dunker; Zhongxue Chen; Liangjiang Wang; Dong Xu; et al. (BMC Bioinform., 2014)

Conformational sampling and structure prediction of multiple interacting loops in soluble and β-barrel membrane proteins using multi-loop distance-guided chain-growth Monte Carlo method. - Ke Tang; Samuel W. K. Wong; Jun S. Liu; Jinfeng Zhang; Jie Liang (Bioinform., 2015)

dslice: an R package for nonparametric testing of associations with application in QTL and gene set analysis. - Chao Ye; Bo Jiang 005; Xuegong Zhang; Jun S. Liu (Bioinform., 2015)

Predicting regulatory variants with composite statistic. - Mulin Jun Li; Zhicheng Pan; Zipeng Liu; Jiexing Wu; Panwen Wang; Yun Zhu; Feng Xu; Zhengyuan Xia; Pak Chung Sham; Jean-Pierre A. Kocher; Miao-Xin Li; Jun S. Liu; et al. (Bioinform., 2016)

Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model. - Xiaoxiao Sun; David Dalpiaz; Di Wu; Jun S. Liu; Wenxuan Zhong; Ping Ma 001 (BMC Bioinform., 2016)

On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting. - Matey Neykov; Jun S. Liu; Tianxi Cai (J. Mach. Learn. Res., 2016)

L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs. - Matey Neykov; Jun S. Liu; Tianxi Cai (J. Mach. Learn. Res., 2016)

Relation discovery and hotspots analysis on diabetes mellitus and obesity with representation model. - Guannan He; Yanchun Liang 001; Yan Chen; William Yang; Jun S. Liu; Mary Qu Yang; Renchu Guan (BIBM, 2017)

CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets. - Yang Li; Alexis A. Jourdain; Sarah E. Calvo; Jun S. Liu; Vamsi K. Mootha (PLoS Comput. Biol., 2017)

A hotspots analysis-relation discovery representation model for revealing diabetes mellitus and obesity. - Guannan He; Yanchun Liang 001; Yan Chen; William Yang; Jun S. Liu; Mary Qu Yang; Renchu Guan (BMC Syst. Biol., 2018)

Systems biology analysis reveals new insights into invasive lung cancer. - Dan Li; William Yang; Carolyn Arthur; Jun S. Liu; Carolina Cruz-Niera; Mary Qu Yang (BMC Syst. Biol., 2018)

Sentence Segmentation for Classical Chinese Based on LSTM with Radical Embedding. - Xu Han; Hongsu Wang; Sanqian Zhang; Qunchao Fu; Jun S. Liu (CoRR, 2018)

On parallelizable Markov chain Monte Carlo algorithms with waste-recycling. - Shihao Yang 002; Yang Chen 063; Espen Bernton; Jun S. Liu (Stat. Comput., 2018)

Characterizing Mutually Exclusive Driver Mutations in Pan-Cancer. - Yifan Zhang; William Yang; Jun S. Liu; Mary Qu Yang (BIBM, 2019)

Generative Parameter Sampler For Scalable Uncertainty Quantification. - Minsuk Shin; Young Lee; Jun S. Liu (CoRR, 2019)

The Wang-Landau Algorithm as Stochastic Optimization and its Acceleration. - Chenguang Dai; Jun S. Liu (CoRR, 2019)

Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks. - Xin Xing; Long Sha; Pengyu Hong; Zuofeng Shang; Jun S. Liu (ICLR, 2020)

NGM: Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks. - Xin Xing; Yu Gui; Chenguang Dai; Jun S. Liu (ICMLA, 2020)

Measurement error models: from nonparametric methods to deep neural networks. - Zhirui Hu; Zheng Tracy Ke; Jun S. Liu (CoRR, 2020)

Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks. - Xin Xing; Yu Gui; Chenguang Dai; Jun S. Liu (CoRR, 2020)

IMMIGRATE: A Margin-Based Feature Selection Method with Interaction Terms. - Ruzhang Zhao; Pengyu Hong; Jun S. Liu (Entropy, 2020)

New Algorithms in RNA Structure Prediction Based on BHG. - Zhendong Liu; Gang Li; Jun S. Liu (Int. J. Pattern Recognit. Artif. Intell., 2020)

Inferring Spatial Organization of Individual Topologically Associated Domains via Piecewise Helical Model. - Rongrong Zhang; Ming Hu 001; Yu Zhu; Zhaohui S. Qin; Ke Deng; Jun S. Liu (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

MiRACLe: an individual-specific approach to improve microRNA-target prediction based on a random contact model. - Pan Wang; Qi Li; Nan Sun; Yibo Gao; Jun S. Liu; Ke Deng; Jie He (Briefings Bioinform., 2021)

Openness weighted association studies: leveraging personal genome information to prioritize non-coding variants. - Shuang Song 006; Nayang Shan; Geng Wang; Xiting Yan; Jun S. Liu; Lin Hou (Bioinform., 2021)

Bayesian Text Classification and Summarization via A Class-Specified Topic Model. - Feifei Wang; Junni L. Zhang; Yichao Li; Ke Deng; Jun S. Liu (J. Mach. Learn. Res., 2021)

A data-adaptive Bayesian regression approach for polygenic risk prediction. - Shuang Song 006; Lin Hou; Jun S. Liu (Bioinform., 2022)

Erratum to: A data-adaptive Bayesian regression approach for polygenic risk prediction. - Shuang Song 006; Lin Hou; Jun S. Liu (Bioinform., 2022)

Multi-Response Heteroscedastic Gaussian Process Models and Their Inference. - Taehee Lee 006; Jun S. Liu (CoRR, 2023)

Convergence rate of multiple-try Metropolis independent sampler. - Xiaodong Yang; Jun S. Liu (Stat. Comput., 2023)

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories. - Haobo Zhang 004; Jianfa Lai; Yicheng Li; Qian Lin; Jun S. Liu (CoRR, 2024)

Generative Multi-Purpose Sampler for Weighted M-estimation. - Minsuk Shin; Shijie Wang; Jun S. Liu (J. Comput. Graph. Stat., 2024)

Varying Coefficient Model via Adaptive Spline Fitting. - Xufei Wang; Bo Jiang 005; Jun S. Liu (J. Comput. Graph. Stat., 2024)

Power of knockoff: The impact of ranking algorithm, augmented design, and symmetric statistic. - Zheng Tracy Ke; Jun S. Liu; Yucong Ma (J. Mach. Learn. Res., 2024)

A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution. - Patrick Gemmell; Timothy B. Sackton; Scott V. Edwards; Jun S. Liu (PLoS Comput. Biol., 2024)