Note: Asterisk * indicates publications on tenure track. Circle o indicates PI’s students or interns. Dagger   indicates publications as a mentor of PI’s students or interns. PI’s name is bold

[41] Ryoma Kawakami◦, Doug Scharre, and Xia Ning*†. Detection of cognitive impairment from eSAGE cognitive data using machine learning. Alzheimer Disease & Associated Disorders – An International Journal, Oct 2023. accepted.

[40] Nitin Nikamanth Appiah Balaji, Jennifer Bogner, Cynthia L. Beaulieu, and Xia Ning*. Traumatic brain injury rehabilitation outcome prediction using machine learning methods. Archives of Rehabilitation Research and Clinical Translation, May 2023. accepted.

[39] Ziqi Chen, Baoyi Zhang, Hongyu Guo, Prashant Emani, Chongming Jiang, Mark Gerstein, Xia Ning*, Chao Cheng, and Martin Renqiang Min. Binding peptide generation for MHC class I proteins with deep reinforcement learning. Bioinformatics, 39(2):btad055, 01 2023.

[38] Ziqi Chen, Oluwatosin R. Ayinde, James R. Fuchs, Huan Sun, and Xia Ning*. G2Retro: Two-step graph generative models for retrosynthesis prediction. Communications Chemistry, 6(1):102, 2023.

[37] Yonghyun Nam, Jae-Seung Yun, Seung Mi Lee, Ji Won Park, Ziqi Chen, Brian Lee, Anurag Verma, Xia Ning*, Li Shen, Anurag Verma, and Dokyoon Kim. Development of complemented comprehensive networks for rapid screening of repurposable drugs applicable to new emerging disease outbreaks. Journal of Translational Medicine, 21(1):415, 2023.

[36] Nader Zidan, Vishal Dey, Katie Allen, John Price, Sarah Renee Zappone, Courtney Hebert, Titus Schleyer, and Xia Ning*. Comorbidities and socio-economic factors affecting COVID-19 severity: A comprehensive study of 776,936 cases and 1,362,545 controls in the State of Indiana, USA. JAMIA Open, 6(1):ooad002, 02 2023.

[35] Tasneem Motiwala, Ping Zhang, Megan Gregory, Naleef Fareed, Xia Ning*, Kevin Coombes, Gabrielle Kokanos, and Courtney Hebert.Review of applied health informatics courses in a multidisciplinary biomedical informatics department. Learning Health Systems, page e10336, Aug. 2022.

[34] Vishal Dey, Raghu Machiraju, and Xia Ning*. Improving compound activity classification via deep transfer and representation learning.ACS Omega, 7(11):9465–9483, March 11 2022.

[33] Ziqi Chen, Bo Peng, Vassilis N. Ioannidis, Mufei Li, George Karypis, and Xia Ning*. A knowledge graph for clinical trials – CTKG.Scientific Reports, 12(1):4724, February 2022.

[32] Wenrong Chen, Elijah N. McCool, Liangliang Sun, Yong Zang, Xia Ning*, and Xiaowen Liu. Evaluation of machine learning models for proteoform retention and migration time prediction in top-down mass spectrometry. Journal of proteome research, 21(7):1736–1747, 2022.

[31] Patrick J. Lawrence and Xia Ning*. Improving MHC Class I antigen processing predictions using representation learning and cleavage site-specific kernels. Cell Reports Methods, 2(9), 2022.

[30] Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, and Xia Ning*. M2: Mixed models with preferences, popularities, and transitions for next-basket recommendation. IEEE Transactions on Knowledge and Data Engineering, 35(4):4033–4046, 2022.

[29] Shinji Tarumi, Wataru Takeuchi, Xia Ning*, Laura Ruppert, Rong Qi, Hideyuki Ban, Daniel H Robertson, Ti- tus K. Schleyer, and Kensaku Kawamoto. Predicting pharmacotherapeutic outcomes for type 2 diabetes: An evaluation of three approaches to leveraging electronic health record data from multiple sources. Journal of Biomedical Informatics, 129:104001, 2022.

[28] Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, and Xia Ning*. A deep generative model for molecule optimization via one fragment modification. Nature Machine Intelligence, 3:1040–1049, Dec. 2021.

[27] Vishal Dey, Peter Krasniak, Minh Nguyen, Clara Lee, and Xia Ning*. Understanding breast implant illness via social media data analysis. Journal of Medical Internet Research Medical Informatics, 9(11):e29768, November 2021.

[26] Ziqi Chen, Martin Renqiang Min, and Xia Ning*. Ranking-based convolutional neural network models for peptide-MHC Class I binding prediction. Frontiers in Molecular Biosciences, 8:128, May 2021.

[25] Jordan R. Hill, Shyam Visweswaran, Xia Ning*, and Titus K. Schleyer. Use, impact, weaknesses, and advanced features of search functions for clinical use in electronic health records: A scoping review. Applied Clinical Informatics, 12:417–428, May 2021.

[24] Lei Wang, Aditi Shendre, Chien-Wei Chiang, Weidan Cao, Xia Ning*, Ping Zhang, Pengyue Zhang, and Lang Li. A pharmacovigilance study of pharmacokinetic drug interactions using a translational informatics discovery approach. British Journal of Clinical Pharmacology, pages 1–11, Feb. 2021.

[23] Arvind Nair, Xia Ning*, and James H Hill. Using recommender systems to improve proactive modeling. Soft- ware and Systems Modeling (SoSyM), pages 1–23, January 2021. (Invited to be presented at MODELS 2021 conference, special collection “SoSyM First” as one of the best SoSyM papers).

[22] Jeffrey A. Skidmore, Lei Xu, Xiuhua Chao, William J. Riggs, Angela Pellittieri, Chloe Vaughan, Xia Ning*, Ruijie Wang, Jianfen Luo, and Shuman He. Prediction of the functional status of the cochlear nerve in individual cochlear implant users using machine learning and electrophysiological measures. Ear and Hearing, 42:180 – 192, January/February 2021.

[21] Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, and Xia Ning*. HAM: Hybrid associations model with pooling for sequential recommendation. IEEE Transactions on Knowledge and Data Engineering, 34(10):4838– 4853, 2021.

[20] Xia Ning*, Ziwei Fan, Evan Burgun, Zhiyun Ren, and Titus Schleyer. Improving information retrieval from electronic health records using dynamic and multi-collaborative filtering. Plos One, 16(8):1–24, 08 2021.

[19] Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, and Xia Ning*. Cognitive biomarker prioritization in Alzheimer’s disease using brain morphometric data. BMC Medical Informatics and Decision Making, 20(1):319, December 2020.

[18] Zhiyun Ren, Bo Peng, Titus Schleyer, and Xia Ning*. Hybrid collaborative filtering methods for recommending search terms to clinicians.Journal of Biomedical Informatics, 113:103635, December 2020.

[17] Melissa A Haendel, Christopher G Chute, Tellen D Bennett, others, and the N3C Consortium. The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment. Journal of the American Medical Informatics Association, 28(3):427–443, Aug 2020. Consortium author.

[16] Abdul Rehman Basharat, Xia Ning*, and Xiaowen Liu. EnvCNN: A Convolutional Neural Network Model for Evaluating Isotopic Envelopesin Top-Down Mass-spectral Deconvolution. Analytical Chemistry, 92(11):7778– 7785, May 2020. PMID: 32356965.

[15] Anqi Zhu, Donglin Zeng, Li Shen, Xia Ning*, Lang Li, and Pengyue Zhang. A super-combo-drug test (supcd-t) to detect adverse drug events and drug interactions from electronic health records in the era of polypharmacy. Statistics in Medicine, 39(10):1458–1472, May 2020.

[14] Heng-Yi Wu, Aditi Shendre, Shijun Zhang, Pengyue Zhang, Lei Wang, Desta Zeruesenay, Luis M. Rocha, Hagit Shatkay, Sara K. Quinney, XiaNing*, and Lang Li. Translational knowledge discovery between drug interactions and pharmacogenetics. Clinical Pharmacology &Therapeutics, 107(4):886–902, April 2020.

[13] Xiaohui Yao, Tiffany Tsang, Qing Sun, Sara Quinney, Pengyue Zhang, Xia Ning*, Lang Li, and Li Shen. Mining and visualizing high-order directional drug interaction effects using the faers database. BMC Medical Informatics and Decision Making, 20(2):1–11, March 2020.

[12] Wen-Hao Chiang, Li Shen, Lang Li, and Xia Ning*. Drug-drug interaction prediction based on co-medication patterns and graph matching.International Journal of Computational Biology and Drug Design, 13(1):36–57, February 2020.

[11]  Yicheng He, Junfeng Liu, and Xia Ning*. Drug selection via joint push and learning to rank. IEEE Transactions on ComputationalBiology and Bioinformatics, 17(1):110–123, January 2020. PMID: 29994481 (The first author is an undergraduate student; the second author is an MS student).

[10] Danai Chasiot, Xiaohui Yao, Pengyue Zhang, Sara K. Quinney, Xia Ning*, Lang Li, and Li Shen. Mining directional drug interaction effects on myopathy using the faers database. Journal of Biomedical and Health Informatics, 23(5):2156–2163, September 2019.

[9] Wen-Hao Chiang, Titus Schleyer, Li Shen, Lang Li, and Xia Ning*. Pattern discovery from high-order drug-drug interaction relations.Journal of Healthcare Informatics Research, 2(3):272–304, September 2018.

[8] CW Chiang, P Zhang, X Wang, L Wang, S Zhang, Xia Ning*, L Shen, SK Quinney, and L Li. Translational high-dimensional drug interaction discovery and validation using health record databases and pharmacokinetics models. Clinical Pharmacology & Therapeutics,103(2):287–295, February 2018.

[7] Xueying Wang, Pengyue Zhang, Chien-Wei Chiang, Hengyi Wu, Li Shen, Xia Ning*, Donglin Zeng, Lei Wang, Sara K. Quinney, Weixing Feng, and Lang Li. Mixture drug-count response model for the high-dimensional drug combinatory effect on myopathy. Statistics in Medicine,37(4):673–686, February 2018.

[6] Junfeng Liu and Xia Ning*. Differential compound prioritization via bi-directional selectivity push with power. Journal of ChemicalInformation and Modeling, 57(12):2958–2975, November 2017. PMID: 29178784.

[5] Junfeng Liu and Xia Ning*. Multi-assay-based compound prioritization via assistance utilization: A machine learning framework.Journal of Chemical Information and Modeling, 57(3):484–498, February 2017. PMID: 28234477.

[4] Fuzhen Zhuang, George Karypis, Xia Ning, Qing He, and Zhongzhi Shi. Multi-view learning via probabilistic latent semantic analysis.Information Sciences, 199:20–30, September 2012.

[3] Xia Ning, Michael Walters, and George Karypis. Improved machine learning models for predicting selective compounds. Journal of Chemical Information and Modelling, 52(1):38–50, 2012.

[2] Xia Ning and George Karypis. In silico structure-activity-relationship (SAR) models from machine learning: a review. Drug Development Research, 72(2):138–146, 2011.

[1] Xia Ning, Huzefa Rangwala, and George Karypis. Multi-assay-based structure-activity-relationship models: Improving structure-activity-relationship models by incorporating activity information from related targets. Journal of Chemical Information and Modeling, 49(11):2444–2456, 2009.