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ORCIDJun S. Liu
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- affiliation: Harvard University, Department of Statistics, Cambridge, MA, USA
- affiliation: Stanford University, Department of Statistics, Stanford, CA, USA
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Journal Articles
- 2024
[j63]Xufei Wang
, Bo Jiang, Jun S. Liu:
Varying Coefficient Model via Adaptive Spline Fitting. J. Comput. Graph. Stat. 33(2): 614-624 (2024)- [j62]Zheng Tracy Ke, Jun S. Liu, Yucong Ma:
Power of knockoff: The impact of ranking algorithm, augmented design, and symmetric statistic. J. Mach. Learn. Res. 25: 3:1-3:67 (2024) - [j61]Patrick Gemmell, Timothy B. Sackton, Scott V. Edwards, Jun S. Liu:
A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution. PLoS Comput. Biol. 20(4): 1011995 (2024) - 2023
- [j60]Xiaodong Yang, Jun S. Liu:
Convergence rate of multiple-try Metropolis independent sampler. Stat. Comput. 33(4): 79 (2023) - 2022
- [j59]Shuang Song, Lin Hou, Jun S. Liu:
A data-adaptive Bayesian regression approach for polygenic risk prediction. Bioinform. 38(7): 1938-1946 (2022) - [j58]Shuang Song, Lin Hou, Jun S. Liu:
Erratum to: A data-adaptive Bayesian regression approach for polygenic risk prediction. Bioinform. 38(7): 2080 (2022) - 2021
- [j57]Pan Wang, Qi Li, Nan Sun, Yibo Gao, Jun S. Liu, Ke Deng, Jie He:
MiRACLe: an individual-specific approach to improve microRNA-target prediction based on a random contact model. Briefings Bioinform. 22(3) (2021) - [j56]Shuang Song, Nayang Shan, Geng Wang, Xiting Yan, Jun S. Liu, Lin Hou:
Openness weighted association studies: leveraging personal genome information to prioritize non-coding variants. Bioinform. 37(24): 4737-4743 (2021) - [j55]Feifei Wang, Junni L. Zhang, Yichao Li, Ke Deng, Jun S. Liu:
Bayesian Text Classification and Summarization via A Class-Specified Topic Model. J. Mach. Learn. Res. 22: 89:1-89:48 (2021) - 2020
- [j54]Ruzhang Zhao, Pengyu Hong, Jun S. Liu:
IMMIGRATE: A Margin-Based Feature Selection Method with Interaction Terms. Entropy 22(3): 291 (2020) - [j53]Zhendong Liu, Gang Li, Jun S. Liu:
New Algorithms in RNA Structure Prediction Based on BHG. Int. J. Pattern Recognit. Artif. Intell. 34(13): 2050031:1-2050031:14 (2020) - [j52]Rongrong Zhang, Ming Hu, Yu Zhu, Zhaohui S. Qin, Ke Deng, Jun S. Liu:
Inferring Spatial Organization of Individual Topologically Associated Domains via Piecewise Helical Model. IEEE ACM Trans. Comput. Biol. Bioinform. 17(2): 647-656 (2020) - 2018
- [j51]Dan Li, William Yang, Carolyn Arthur, Jun S. Liu, Carolina Cruz-Niera, Mary Qu Yang:
Systems biology analysis reveals new insights into invasive lung cancer. BMC Syst. Biol. 12(7): 47-53 (2018) - [j50]Guannan He, Yanchun Liang, Yan Chen, William Yang, Jun S. Liu, Mary Qu Yang, Renchu Guan:
A hotspots analysis-relation discovery representation model for revealing diabetes mellitus and obesity. BMC Syst. Biol. 12(7): 75-85 (2018) - [j49]Shihao Yang, Yang Chen, Espen Bernton, Jun S. Liu:
On parallelizable Markov chain Monte Carlo algorithms with waste-recycling. Stat. Comput. 28(5): 1073-1081 (2018) - 2017
- [j48]Yang Li, Alexis A. Jourdain, Sarah E. Calvo, Jun S. Liu, Vamsi K. Mootha:
CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets. PLoS Comput. Biol. 13(7) (2017) - 2016
- [j47]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, Junwen Wang:
Predicting regulatory variants with composite statistic. Bioinform. 32(18): 2729-2736 (2016) - [j46]Xiaoxiao Sun, David Dalpiaz, Di Wu, Jun S. Liu, Wenxuan Zhong, Ping Ma:
Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model. BMC Bioinform. 17: 324 (2016) - [j45]Matey Neykov, Jun S. Liu, Tianxi Cai:
On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting. J. Mach. Learn. Res. 17: 70:1-70:32 (2016) - [j44]Matey Neykov, Jun S. Liu, Tianxi Cai:
L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs. J. Mach. Learn. Res. 17: 87:1-87:37 (2016) - 2015
- [j43]Chao Ye, Bo Jiang, Xuegong Zhang, Jun S. Liu:
dslice: an R package for nonparametric testing of associations with application in QTL and gene set analysis. Bioinform. 31(11): 1842-1844 (2015) - [j42]Ke Tang, Samuel W. K. Wong, Jun S. Liu, Jinfeng Zhang, Jie Liang:
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. Bioinform. 31(16): 2646-2652 (2015) - 2014
- [j41]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, Youping Deng, Weida Tong, Mary Qu Yang:
Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms. BMC Bioinform. 15(S-17): I1 (2014) - [j40]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, Hamid R. Arabnia, Weida Tong, Mary Qu Yang:
Identification of genes and pathways involved in kidney renal clear cell carcinoma. BMC Bioinform. 15(S-17): S2 (2014) - 2013
- [j39]Bo Jiang, Jun S. Liu, Martha L. Bulyk:
Bayesian hierarchical model of protein-binding microarray k-mer data reduces noise and identifies transcription factor subclasses and preferred k-mers. Bioinform. 29(11): 1390-1398 (2013) - [j38]Rajesh Chowdhary, Jinfeng Zhang, Sin Lam Tan, Daniel E. Osborne, Vladimir B. Bajic, Jun S. Liu:
PIMiner: a web tool for extraction of protein interactions from biomedical literature. Int. J. Data Min. Bioinform. 7(4): 450-462 (2013) - [j37]Ming Hu, Ke Deng, Zhaohui S. Qin, Jesse R. Dixon, Siddarth Selvaraj, Jennifer Fang, Bing Ren, Jun S. Liu:
Bayesian Inference of Spatial Organizations of Chromosomes. PLoS Comput. Biol. 9(1) (2013) - [j36]Ming Hu, Ke Deng, Zhaohui S. Qin, Jun S. Liu:
Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data. Quant. Biol. 1(2): 156-174 (2013) - 2012
- [j35]Ming Hu, Yu Zhu, Jeremy M. G. Taylor, Jun S. Liu, Zhaohui S. Qin:
Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq. Bioinform. 28(1): 63-68 (2012) - [j34]Sentil Balaji, Charles Mcclendon, Rajesh Chowdhary, Jun S. Liu, Jinfeng Zhang:
IMID: integrated molecular interaction database. Bioinform. 28(5): 747-749 (2012) - [j33]Jianxing Feng, Clifford A. Meyer, Qian Wang, Jun S. Liu, Xiaole Shirley Liu, Yong Zhang:
GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. Bioinform. 28(21): 2782-2788 (2012) - [j32]Ming Hu, Ke Deng, Siddarth Selvaraj, Zhaohui S. Qin, Bing Ren, Jun S. Liu:
HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinform. 28(23): 3131-3133 (2012) - [j31]Ke Deng, Yang Li, Weiping Zhu, Zhi Geng, Jun S. Liu:
On Delay Tomography: Fast Algorithms and Spatially Dependent Models. IEEE Trans. Signal Process. 60(11): 5685-5697 (2012) - 2010
- [j30]Hanchang Sun, Yuan Yuan, Yibo Wu, Hui Liu, Jun S. Liu, Hongwei Xie:
Tmod: toolbox of motif discovery. Bioinform. 26(3): 405-407 (2010) - [j29]Rajesh Chowdhary, Vladimir B. Bajic, Difeng Dong, Limsoon Wong, Jun S. Liu:
Genome-wide analysis of regions similar to promoters of histone genes. BMC Syst. Biol. 4(S-1): S4 (2010) - [j28]Wei Zhang, Jun Zhu, Eric E. Schadt, Jun S. Liu:
A Bayesian Partition Method for Detecting Pleiotropic and Epistatic eQTL Modules. PLoS Comput. Biol. 6(1) (2010) - 2009
- [j27]Rajesh Chowdhary, Jinfeng Zhang, Jun S. Liu:
Bayesian inference of protein-protein interactions from biological literature. Bioinform. 25(12): 1536-1542 (2009) - [j26]Patrycja Vasilyev Missiuro, Kesheng Liu, Lihua Zou, Brian C. Ross, Guoyan Zhao, Jun S. Liu, Hui Ge:
Information Flow Analysis of Interactome Networks. PLoS Comput. Biol. 5(4) (2009) - 2008
- [j25]Guo-Cheng Yuan, Jun S. Liu:
Genomic Sequence Is Highly Predictive of Local Nucleosome Depletion. PLoS Comput. Biol. 4(1) (2008) - [j24]Lihua Zou, Sira Sriswasdi, Brian C. Ross, Patrycja Vasilyev Missiuro, Jun S. Liu, Hui Ge:
Systematic Analysis of Pleiotropy in C. elegans Early Embryogenesis. PLoS Comput. Biol. 4(2) (2008) - 2007
- [j23]Xiaodan Fan, Jun Zhu, Eric E. Schadt, Jun S. Liu:
Statistical power of phylo-HMM for evolutionarily conserved element detection. BMC Bioinform. 8 (2007) - [j22]Yuan Yuan, Lei Guo, Lei Shen, Jun S. Liu:
Predicting Gene Expression from Sequence: A Reexamination. PLoS Comput. Biol. 3(11) (2007) - [j21]Gopi Goswami, Jun S. Liu:
On learning strategies for evolutionary Monte Carlo. Stat. Comput. 17(1): 23-38 (2007) - 2006
- [j20]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:
Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. BMC Bioinform. 7: 197 (2006) - [j19]Erin M. Conlon, Joon J. Song, Jun S. Liu:
Bayesian models for pooling microarray studies with multiple sources of replications. BMC Bioinform. 7: 247 (2006) - [j18]Jinfeng Zhang, Jun S. Liu:
On Side-Chain Conformational Entropy of Proteins. PLoS Comput. Biol. 2(12) (2006) - 2005
- [j17]Kui Zhang, Zhaohui S. Qin, Ting Chen, Jun S. Liu, Michael S. Waterman, Fengzhu Sun:
HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms. Bioinform. 21(1): 131-134 (2005) - [j16]Pengyu Hong, Xiaole Shirley Liu, Qing Zhou, Xin Lu, Jun S. Liu, Wing Hung Wong:
A boosting approach for motif modeling using ChIP-chip data. Bioinform. 21(11): 2636-2643 (2005) - [j15]Dongsheng Che, Shane T. Jensen, Liming Cai, Jun S. Liu:
BEST: Binding-site Estimation Suite of Tools. Bioinform. 21(12): 2909-2911 (2005) - [j14]Shane T. Jensen, Lei Shen, Jun S. Liu:
Combining phylogenetic motif discovery and motif clustering to predict co-regulated genes. Bioinform. 21(20): 3832-3839 (2005) - [j13]Wenxuan Zhong, Peng Zeng, Ping Ma, Jun S. Liu, Michael Yu Zhu:
RSIR: regularized sliced inverse regression for motif discovery. Bioinform. 21(22): 4169-4175 (2005) - 2004
- [j12]Qing Zhou, Jun S. Liu:
Modeling within-motif dependence for transcription factor binding site predictions. Bioinform. 20(6): 909-916 (2004) - [j11]Shane T. Jensen, Jun S. Liu:
BioOptimizer: a Bayesian scoring function approach to motif discovery. Bioinform. 20(10): 1557-1564 (2004) - [j10]Andrew F. Neuwald, Jun S. Liu:
Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model. BMC Bioinform. 5: 157 (2004) - [j9]Haiyan Huang, Ming-Chih J. Kao, Xianghong Jasmine Zhou, Jun S. Liu, Wing Hung Wong:
Determination of Local Statistical Significance of Patterns in Markov Sequences with Application to Promoter Element Identification. J. Comput. Biol. 11(1): 1-14 (2004) - [j8]Yueyi Liu, Liping Wei, Serafim Batzoglou, Douglas L. Brutlag, Jun S. Liu, Xiaole Shirley Liu:
A suite of web-based programs to search for transcriptional regulatory motifs. Nucleic Acids Res. 32(Web-Server-Issue): 204-207 (2004) - 2002
- [j7]Rong Chen, Jun S. Liu, Xiaodong Wang:
Convergence analyses and comparisons of Markov chain Monte Carlo algorithms in digital communications. IEEE Trans. Signal Process. 50(2): 255-270 (2002) - [j6]Xiaodong Wang, Rong Chen, Jun S. Liu:
Monte Carlo Bayesian Signal Processing for Wireless Communications. J. VLSI Signal Process. 30(1-3): 89-105 (2002) - 2000
- [j5]Scott C. Schmidler, Jun S. Liu, Douglas L. Brutlag:
Bayesian Segmentation of Protein Secondary Structure. J. Comput. Biol. 7(1-2): 233-248 (2000) - [j4]Rong Chen, Xiaodong Wang, Jun S. Liu:
Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering. IEEE Trans. Inf. Theory 46(6): 2079-2094 (2000) - 1999
- [j3]Jun S. Liu, Charles E. Lawrence:
Bayesian inference on biopolymer models. Bioinform. 15(1): 38-52 (1999) - 1998
- [j2]Jun Zhu, Jun S. Liu, Charles E. Lawrence:
Bayesian adaptive sequence alignment algorithms. Bioinform. 14(1): 25-39 (1998) - 1996
- [j1]Jun S. Liu:
Metropolized independent sampling with comparisons to rejection sampling and importance sampling. Stat. Comput. 6(2): 113-119 (1996)
Conference and Workshop Papers
- 2020
- [c16]Xin Xing, Long Sha, Pengyu Hong, Zuofeng Shang, Jun S. Liu:
Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks. ICLR 2020 - [c15]Xin Xing, Yu Gui, Chenguang Dai, Jun S. Liu:
NGM: Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks. ICMLA 2020: 148-152 - 2019
- [c14]Yifan Zhang, William Yang, Jun S. Liu, Mary Qu Yang:
Characterizing Mutually Exclusive Driver Mutations in Pan-Cancer. BIBM 2019: 2013-2020 - 2017
- [c13]Guannan He, Yanchun Liang, Yan Chen, William Yang, Jun S. Liu, Mary Qu Yang, Renchu Guan:
Relation discovery and hotspots analysis on diabetes mellitus and obesity with representation model. BIBM 2017: 952-957 - 2008
- [c12]Dongsheng Che, Guojun Li, Shane T. Jensen, Jun S. Liu, Ying Xu:
PFP: A Computational Framework for Phylogenetic Footprinting in Prokaryotic Genomes. ISBRA 2008: 110-121 - 2007
- [c11]Guo-Cheng Yuan, Jun S. Liu:
Statistial Analysis of nucleosome occupancy and histone modification data. BIBE 2007: 8 - [c10]Jiajun Gu, Jun S. Liu:
Bayesian Biclustering of Microarray Data. BIOCOMP 2007: 113-120 - 2003
- [c9]Jun S. Liu:
BPPS: An Algorithm for Analyzing Protein Sequence Alignments. CSB 2003: 28 - [c8]Xin Lu, Wen Zhang, Zhaohui S. Qin, Jun S. Liu:
Statistical Resynchronization and Detection of Periodic Transcripts. CSB 2003: 394-395 - 2002
- [c7]Tianhua Niu, Xin Lu, Hosung Kang, Zhaohui S. Qin, Jun S. Liu:
Haplotype Inference and Its Application in Linkage Disequilibrium Mapping. Computational Methods for SNPs and Haplotype Inference 2002: 48-61 - [c6]Kui Zhang, Ting Chen, Michael S. Waterman, Zhaohui S. Qin, Jun S. Liu, Fengzhu Sun:
Dynamic Programming Algorithms for Haplotype Block Partitioning and Tag SNP Selection Using Haplotype Data or Genotype Data. Computational Methods for SNPs and Haplotype Inference 2002: 96-112 - 2001
- [c5]X. Liu, Douglas L. Brutlag, Jun S. Liu:
BioProspector: Discovering Conserved DNA Motifs in Upstream Regulatory Regions of Co-Expressed Genes. Pacific Symposium on Biocomputing 2001: 127-138 - 2000
- [c4]Jason Cong, Tianming Kong, Faming Liang, Jun S. Liu, Wing Hung Wong, Dongmin Xu:
Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application. ASP-DAC 2000: 277-282 - 1999
- [c3]Jason Cong, Tianming Kong, Dongmin Xu, Faming Liang, Jun S. Liu, Wing Hung Wong:
Relaxed Simulated Tempering for VLSI Floorplan Designs. ASP-DAC 1999: 13-16 - 1997
- [c2]Jun Zhu, Jun S. Liu, Charles E. Lawrence:
Bayesian Adaptive Alignment and Inference. ISMB 1997: 358-368 - 1994
- [c1]Charles E. Lawrence, Stephen F. Altschul, John C. Wootton, Mark S. Boguski, Andrew F. Neuwald, Jun S. Liu:
A Gibbs Sampler for the Detection of Subtle Motifs in Multiple Sequences. HICSS (5) 1994: 245-254
Parts in Books or Collections
- 2011
- [p2]Bo Jiang, Jun S. Liu:
Statistical Learning and Modeling of TF-DNA Binding. Handbook of Statistical Bioinformatics 2011: 55-72 - 2001
- [p1]Jun S. Liu, Rong Chen, Tanya Logvinenko:
A Theoretical Framework for Sequential Importance Sampling with Resampling. Sequential Monte Carlo Methods in Practice 2001: 225-246
Informal and Other Publications
- 2024
- [i8]Haobo Zhang, Jianfa Lai, Yicheng Li, Qian Lin, Jun S. Liu:
Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories. CoRR abs/2412.18756 (2024) - 2023
- [i7]Taehee Lee, Jun S. Liu:
Multi-Response Heteroscedastic Gaussian Process Models and Their Inference. CoRR abs/2308.15370 (2023) - 2020
- [i6]Zhirui Hu, Zheng Tracy Ke, Jun S. Liu:
Measurement error models: from nonparametric methods to deep neural networks. CoRR abs/2007.07498 (2020) - [i5]Xin Xing, Yu Gui, Chenguang Dai, Jun S. Liu:
Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks. CoRR abs/2010.06175 (2020) - 2019
- [i4]Minsuk Shin, Young Lee, Jun S. Liu:
Generative Parameter Sampler For Scalable Uncertainty Quantification. CoRR abs/1905.12440 (2019) - [i3]Chenguang Dai, Jun S. Liu:
The Wang-Landau Algorithm as Stochastic Optimization and its Acceleration. CoRR abs/1907.11985 (2019) - 2018
- [i2]Ruzhang Zhao, Pengyu Hong, Jun S. Liu:
IMMIGRATE: A Margin-based Feature Selection Method with Interaction Terms. CoRR abs/1810.02658 (2018) - [i1]Xu Han, Hongsu Wang, Sanqian Zhang, Qunchao Fu, Jun S. Liu:
Sentence Segmentation for Classical Chinese Based on LSTM with Radical Embedding. CoRR abs/1810.03479 (2018)
Coauthor Index
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