Publications

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 Reports.

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.

Xinjun Li, F Feng, Hongxi Pu, W Leung, J Liu (2021). scHiCTools: a computational toolbox for analyzing single-cell Hi-C data. PLOS Computational Biology.

PDF Code Project

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. In Genome Res.

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 Computational Biology.

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. In Cell Reports.

J Liu, Y Huang, R Singh, J Vert, W Noble (2019). Jointly embedding multiple single-cell omics measurements. In The Workshop on Algorithms in Bioinformatics.

PDF Code Project

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.

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

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

Project Source Document

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. In Scientific Reports.

PDF Code Project

J Liu, C Zhang, D Page (2016). Multiple Testing under Dependence via Graphical Models. In Annals of Applied Statistics.

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. In JMLR.

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.

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. In Acad Radiol.

Preprint Project

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

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. In J. of Medical Imaging.

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. In AMIA Joint Summits.

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.

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. In AMIA Symposium.

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

PDF Code Project

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

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

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

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. In AMIA Symposium.

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

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

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. In UAI.

PDF Code Project

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

PDF Code Project

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

J Liu*, Z Hu*, S Tan (2009). Cross-Sectional Stock Return Analysis Using Support Vector Regression. In Applied Economics Letters.

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. In Nucleic Acids Res.

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