Publications

R Haliyur, D Parkinson, F Ma, J Xu, Q Li, Y Huang, L Tsoi,, R Bogle, J Liu, J Gudjonsson, R C Rao (2024). Liquid biopsy for proliferative diabetic retinopathy: single-cell transcriptomics of human vitreous reveals inflammatory T cell signature. Ophthalmology Science.

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Y Tao, F Feng, X Luo, C Reihsmann, A Hopkirk, J Cartailler, M Brissova, S Parker, D Saunders, J Liu (2024). CNTools: A computational toolbox for cellular neighborhood analysis from multiplexed images. PLoS Comput. Biol..

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S Wang, S Chakraborty, Y Fu, M Lee, J Liu, J Waldhaus (2024). 3D reconstruction of the mouse cochlea from scRNA-seq data suggests morphogen-based principles in apex-to-base specification. Dev. Cell.

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J Waldhaus*, Linghua Jiang*, L Liu, J Liu, R Duncan (2024). Mapping the developmental potential of mouse inner ear organoids at single-cell resolution. iScience.

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J Walker, D Saunders, V Rai, H Chen, P Orchard, C Dai, Y Pettway, A Hopkirk, C Reihsmann, Y Tao, S Fan, S Shrestha, A Varshney, LE. Petty, J Wright, C Ventresca, S Agarwala, R Aramandla, G Poffenberger, R Jenkins, S Mei, N Hart, S Phillips, H Kang, D Greiner, L Shultz, R Bottino, J Liu, J Below, The HPAP Consortium, S Parker, A Powers, M Brissova (2023). Genetic risk converges on regulatory networks mediating early type 2 diabetes. Nature.

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Z Zhang, F Fang, Y Qiu, J Liu (2023). A generalizable framework to comprehensively predict epigenome, chromatin organization, and transcriptome. Nucleic Acids Res.

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F Feng, F Tang, Y Gao, D Zhu, T Li, S Yang, Y Yao, Y Huang, J Liu (2022). GenomicKB: a knowledge graph for the human genome. Nucleic Acids Res.

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Y Huang, B Wang, J Liu (2022). NucleoMap: a computational tool for identifying nucleosomes in ultra-high resolution contact maps. PLoS Comput. Biol.

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Z Zhang, F Feng, J Liu (2022). Characterizing collaborative transcription regulation with a graph-based deep learning approach. PLoS Comput. Biol.

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F Feng, Y Yao, D Wang, X Zhang, J Liu (2022). Connecting high-resolution 3D chromatin organization with epigenomics. Nat. Commun.

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Q Li, Y Huang, J Xu, F Mao, B Zhou, L Sun, B Basinski, M Aksu, J Liu, Y Dou, R Rao (2021). p53 inactivation unmasks histone methylation-independent and cytoplasmic-dependent WDR5 functions that drive self-renewal and differentiation of pluripotent stem cells. Stem Cell Rep..

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P Himadewi, X Wang, F Feng, H Gore, Y Liu, L Yu, R Kurita, Y Nakamura, G Pfeifer, J Liu, X Zhang (2021). 3′HS1 CTCF binding site in human β-globin locus regulates fetal hemoglobin expression. eLife.

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X Li, F Feng, H Pu, W Leung, J Liu (2021). scHiCTools: a computational toolbox for analyzing single-cell Hi-C data. PLoS Comput. Biol.

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S Wang, M P. Lee, S Jones, J Liu, J Waldhaus (2021). Mapping the regulatory landscape of auditory hair cells from single-cell multi-omics data. Genome Res..

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H Kim, G Yardımcı, G Bonora, V Ramani, J Liu, R Qiu, C Lee, J Hesson, C Ware, J Shendure, Z Duan, W Noble (2020). Capturing cell type-specific chromatin structural patterns by applying topic modeling to single-cell Hi-C data. PLoS Comput. Biol..

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Q Li, F Mao, B Zhou, Y Huang, Z Zou, A DenDekker, J Xu, S Hou, J Liu, Y Dou, R Rao (2020). p53 Integrates Temporal WDR5 Inputs during Neuroectoderm and Mesoderm Differentiation of Mouse Embryonic Stem Cells. Cell Rep..

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J Liu, Y Huang, R Singh, J Vert, W Noble (2019). Jointly embedding multiple single-cell omics measurements. WABI.

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J Kim, X He, J Liu, Z Duan, T Kim, J Gerard, B Kim, M Pillai, W Lane, W Noble, B Budnik, T Waldman (2019). Systematic proteomics of endogenous human cohesin reveals an interaction with diverse splicing factors and RNA binding proteins required for mitotic progression. In Journal of Biological Chemistry.

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Z Kuang, S Geng, J Liu, S Wright, D Page (2018). Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI.

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J Liu, D Lin, G Yardimci, W Noble (2018). Unsupervised embedding of single-cell Hi-C data. In ISMB.

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J Liu, J Halloran, J Bilmes, R Daza, C Lee, E Mahen, D Prunkard, C Song, S Blau, M Dorschner, V Gadi, J Shendure, A Blau, W Noble (2017). Comprehensive statistical inference of the clonal structure of cancer from multiple biopsies. Sci. Rep..

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J Liu, C Zhang, D Page (2016). Multiple Testing under Dependence via Graphical Models. Ann. Appl. Stat.

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J Fan, Y Wu, M Yuan, D Page, J Liu, I Ong, P Peissig, ES Burnside (2016). Structure-leveraged Methods in Breast Cancer Risk Prediction. JMLR.

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Y Wu, C Abbey, J Liu, I Ong, P Peissig, A Onitilo, J Fan, M Yuan, E Burnside (2016). Discriminatory power of common genetic variants in personalized breast cancer diagnosis. In SPIE Medical Imaging conference.

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ES Burnside, J Liu, Y Wu, A Onitilo, C McCarty, D Page, P Peissig, A Trentham-Dietz, T Kitchner, J Fan, M Yuan (2016). Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy. Acad. Radiol..

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J Weiss, F Kuusisto, K Boyd, J Liu, D Page (2015). Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. AMIA Symposium.

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Y Wu, C Abbey, X Chen, J Liu, D Page, O Algoz, P Peissig, A Onitilo, ES Burnside (2015). Developing a Utility Decision Framework to Evaluate Predictive Models in Breast Cancer Risk Estimation. J. Med. Imaging.

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J Liu, Y Wu, I Ong, D Page, P Peissig, C McCarty, A Onitilo, ES Burnside (2015). Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution. AMIA Joint Summits.

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Y Wu, J Liu, A del Rio, D Page, O Alagoz, P Peissig, A Onitilo, ES Burnside (2015). Developing a Clinical Utility Framework to Evaluate Prediction Models in Radiogenomics. In SPIE Medical Imaging conference.

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Y Wu, J Liu, D Page, P Peissig, C McCarty, A Onitilo, ES Burnside (2014). Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction. AMIA Symposium.

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J Liu, C Zhang, ES Burnside, D Page (2014). Multiple Testing under Dependence via Semiparametric Graphical Models. ICML.

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J Liu, D Page, P Peissig, C McCarty, A Onitilo, A Trentham-Dietz, ES Burnside (2014). New Genetic Variants Improve Personalized Breast Cancer Diagnosis. AMIA-TBI.

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J Liu, C Zhang, ES Burnside, D Page (2014). Learning Heterogeneous Hidden Markov Random Fields. AISTATS.

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J Liu, D Page (2013). Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models. NIPS.

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J Liu, D Page, P Peissig, C McCarty, A Onitilo, A Trentham-Dietz, ES Burnside (2013). Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. AMIA Symposium.

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J Liu, D Page (2013). Structure Learning of Undirected Graphical Models with Contrastive Divergence. ICML Workshop.

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J Liu, ES Burnside, D Page (2013). Predicting Breast Cancer and Prostate Cancer Susceptibility from Single Nucleotide Polymorphisms. ICML Workshop.

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J Liu, C Zhang, C McCarty, P Peissig, ES Burnside, D Page (2012). Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies. UAI.

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J Liu, C Zhang, C McCarty, P Peissig, ES Burnside, D Page (2012). High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. AISTAT.

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J Liu, H Vidaillet, ES Burnside, D Page (2012). A Collective Ranking Method for Genome-wide Association Studies. ACM-BCB.

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J Liu*, Z Hu*, S Tan (2009). Cross-Sectional Stock Return Analysis Using Support Vector Regression. Appl. Econ. Lett..

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J Wan, S Kang, C Tang, Y Ren, J Liu, X Gao, A Banerjee, L Ellis, T Li (2008). Meta-prediction of Phosphorylation Sites with Weighted Voting and Restricted Grid Search Parameter Selection. Nucleic Acids Res..

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J Liu, S Kang, C Tang, LB Ellis, T Li (2007). Meta-prediction of Protein Subcellular Localization with Reduced Voting. Nucleic Acids Res..

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