Statistical Methodology

Ha, M. J., Banerjee, S., Akbani, R., Liang, H., Mills, G. B., Do, K. A.,& Baladandayuthapani, V. 

Personalized Integrated Network Modeling of the Cancer Proteome Atlas. 

Scientific Reports, 8(1), 14924.(2018)

PAPER   SHINYAPP 

Ni Y., Stingo F.C., Ha M. J., Akbani R., & Baladandayuthapani V. 

Bayesian hierarchical varying-sparsity regression models with application to cancer proteogenomics. 

Journal of the American Statistical Association. 114(525), 48-60.(2019)

PAPER 

Kim J., Do K., Ha M. J., & Peterson C.B.

Bayesian inference of hub nodes across multiple networks. 

Biometrics, 75(1), 172-182.(2019)

PAPER 

 Liu Q, Ha M. J., Bhattacharyya R. Garmire L., Baladandayuthapani V. 

 Network-Based Matching of Patients and Targeted Therapies for Precision Oncology.

Pacific Symposium on Biocomputing 2020.(2020)

PAPER 

 Bhattacharyya R., Ha M. J.*, Liu Q., Akbni R., Liang H., Baladandayuthapani V.

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome.

Journal of Clinical Oncology, Clinical Cancer Informatics 4:399-411.(2020)

PAPER   SHINYAPP  CODE 

Ha, M.J.*, Kim, J., Galloway-Pena, J., Do, K.A. and Peterson, C.B.

 Compositional zero-inflated network estimation for microbiome data.

BMC bioinformatics, 21(21), pp.1-20. (2020)

PAPER   SOFTWARE 

Ha, M.J.* and Sun, W.

 Estimation of high-dimensional directed acyclic graphs with surrogate intervention.

Biostatistics, 21(4), pp.659-675.(2020)

PAPER   SOFTWARE 

Ha, M.J.*, Stingo, F.C. and Baladandayuthapani, V.

Bayesian Structure Learning in Multilayered Genomic Networks. 

Journal of the American Statistical Association, pp.1-14.(2021)

PAPER   SOFTWARE 

Long, J.P. Ha ,M.J. 

Sample Selection Bias in Evaluation of Prediction Performance of Causal Models. Statistical Analysis and Data Mining

Statistical Analysis and Data Mining 15 (1), 5-14. (2021+)

PAPER 

Saha, A., Ha, M. J., Acharyya, S., & Baladandayuthapani, V.

A Bayesian precision medicine framework for calibrating individualized therapeutic indices in cancer. 

The Annals of Applied Statistics, 16(4), 2055-2082.(2022)

PAPER 

Huang L., Wang J., Fang B., Meric-Bernstam F.M., Roth J.A., Ha, M.J.* 

CombPDX: a unified statistical framework for evaluating drug synergism in patient-derived xenografts. 

Scientific Reports 12 (1),1-10. (2022)

PAPER   SOFTWARE 

Long, J. P., Zhu, H., Do, K. A., & Ha, M. J. 

Estimating causal effects with hidden confounding using instrumental variables and environments. 

Electronic Journal of Statistics, 17(2), 2849-2879.(2023)

PAPER 

Huang, L., Long, J. P., Irajizad, E., Doecke, J. D., Do, K. A., & Ha, M. J.*

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes.

Bioinformatics, 39(1), btad023.(2023)

PAPER 

Chakraborty, M., Baladandayuthapani, V., Bhadra, A., & Ha, M. J.*

Bayesian robust learning in chain graph models for integrative pharmacogenomics.

The Annals of Applied Statistics, Ann. Appl. Stat. 18(4), 3274-3296. (2024)

PAPER 

Seo, D., Baladandayuthapani, V., Park, T., & Ha, M. J. 

Bayesian multilayered mediation analysis for cancer pharmacogenomics. 

Stat, 13(4), e70020.  (2024).

PAPER