Publications

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

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. Comprehensive statistical inference of the clonal structure of cancer from multiple biopsies. In Scientific Reports, 2017.

PDF Code Project Cancer Genomics Dynamic Graphical Models

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

PDF Project Multiple Testing Graphic Model GWAS

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

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

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

Preprint Project

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

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

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

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

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

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

PDF Code Project

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

PDF Project Marco Ramoni Distinguished Paper Award

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

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

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

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

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

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

PDF Code Project

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

PDF Code Project

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

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

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

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