Lue Ping Zhao

12.9k total citations · 3 hit papers
162 papers, 9.0k citations indexed

About

Lue Ping Zhao is a scholar working on Genetics, Molecular Biology and Immunology. According to data from OpenAlex, Lue Ping Zhao has authored 162 papers receiving a total of 9.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Genetics, 47 papers in Molecular Biology and 26 papers in Immunology. Recurrent topics in Lue Ping Zhao's work include Genetic Associations and Epidemiology (26 papers), Gene expression and cancer classification (20 papers) and Statistical Methods and Bayesian Inference (18 papers). Lue Ping Zhao is often cited by papers focused on Genetic Associations and Epidemiology (26 papers), Gene expression and cancer classification (20 papers) and Statistical Methods and Bayesian Inference (18 papers). Lue Ping Zhao collaborates with scholars based in United States, South Africa and Sweden. Lue Ping Zhao's co-authors include James M. Robins, Andrea Rotnitzky, Ross L. Prentice, Stuart R. Lipsitz, Shuying Sue Li, Alan Aderem, Thomas R. Hawn, John A. Hansen, Marta Janer and Wenhong Fan and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nature Genetics.

In The Last Decade

Lue Ping Zhao

158 papers receiving 8.7k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Estimation of Regression Coefficients When Some Regressors are not Always Observed

1994 1.7k citations Lue Ping Zhao et al. Journal of the American Statistical Association profile →
Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data

1995 1.1k citations Lue Ping Zhao et al. Journal of the American Statistical Association profile →
A Common Dominant TLR5 Stop Codon Polymorphism Abolishes Flagellin Signaling and Is Associated with Susceptibility to Legionnaires' Disease

2003 467 citations Thomas R. Hawn, Lue Ping Zhao et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Lue Ping Zhao United States	42	3.3k	1.8k	1.4k	1.0k	927	162	9.0k
Steven G. Self United States	48	1.8k 0.5×	1.3k 0.7×	2.2k 1.6×	1.7k 1.6×	1.7k 1.8×	119	10.6k
Ying Yuan United States	57	3.2k 1.0×	2.4k 1.4×	1.0k 0.7×	1.7k 1.6×	458 0.5×	378	10.8k
Vernon T. Farewell United Kingdom	72	2.5k 0.8×	1.3k 0.7×	4.4k 3.2×	1.4k 1.4×	763 0.8×	287	18.5k
Michael A. Proschan United States	49	1.4k 0.4×	798 0.5×	1.4k 1.0×	1.3k 1.2×	559 0.6×	153	15.2k
Daniel F. Heitjan United States	61	1.6k 0.5×	2.6k 1.5×	834 0.6×	1.5k 1.5×	1.3k 1.4×	229	12.7k
Cyrus R. Mehta United States	38	2.1k 0.6×	1.5k 0.8×	301 0.2×	652 0.6×	334 0.4×	137	8.5k
Laurence S. Freedman Israel	66	2.3k 0.7×	1.6k 0.9×	313 0.2×	989 1.0×	1.3k 1.4×	272	18.0k
Jing Qin United States	49	2.2k 0.7×	587 0.3×	432 0.3×	632 0.6×	292 0.3×	231	7.1k
Ram C. Tiwari United States	27	1.5k 0.5×	2.6k 1.5×	518 0.4×	1.2k 1.2×	772 0.8×	223	11.9k
D. Y. Lin United States	50	6.1k 1.8×	936 0.5×	237 0.2×	1.3k 1.2×	1.1k 1.2×	146	15.0k

Countries citing papers authored by Lue Ping Zhao

Since Specialization

Citations

This map shows the geographic impact of Lue Ping Zhao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lue Ping Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lue Ping Zhao more than expected).

Fields of papers citing papers by Lue Ping Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lue Ping Zhao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lue Ping Zhao. The network helps show where Lue Ping Zhao may publish in the future.

Co-authorship network of co-authors of Lue Ping Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Lue Ping Zhao. A scholar is included among the top collaborators of Lue Ping Zhao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lue Ping Zhao. Lue Ping Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Zhao, Lue Ping, et al.. (2025). The Longitudinal Relationship between Adolescents’ Prosocial Behavior and Well-Being: A Cross-Lagged Panel Network Analysis. Journal of Youth and Adolescence. 54(6). 1428–1441. 1 indexed citations

Zhao, Lue Ping, George K. Papadopoulos, Jay S. Skyler, et al.. (2024). Progression to type 1 diabetes in the DPT-1 and TN07 clinical trials is critically associated with specific residues in HLA-DQA1-B1 heterodimers. Diabetologia. 67(11). 2481–2493.

Zhao, Lue Ping, Terry P. Lybrand, Peter B. Gilbert, et al.. (2022). Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy. Scientific Reports. 12(1). 19089–19089. 7 indexed citations

Zhao, Lue Ping, Terry P. Lybrand, Peter B. Gilbert, et al.. (2021). Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020—March 2021) Using a Statistical Learning Strategy. Viruses. 14(1). 9–9. 9 indexed citations

Leger, Kasey J., Kara L. Cushing‐Haugen, John A. Hansen, et al.. (2016). Clinical and Genetic Determinants of Cardiomyopathy Risk among Hematopoietic Cell Transplantation Survivors. Biology of Blood and Marrow Transplantation. 22(6). 1094–1101. 33 indexed citations

Zhao, Lue Ping & Hamid Bolouri. (2016). Object-oriented regression for building predictive models with high dimensional omics data from translational studies. Journal of Biomedical Informatics. 60. 431–445. 16 indexed citations

Chen, Ying Qing, Nan Hu, Su‐Chun Cheng, Philippa Musoke, & Lue Ping Zhao. (2012). Estimating Regression Parameters in an Extended Proportional Odds Model. Journal of the American Statistical Association. 107(497). 318–330. 2 indexed citations

Warren, Edus H., Xinyi Cindy Zhang, Shuying Li, et al.. (2012). Effect of MHC and non-MHC donor/recipient genetic disparity on the outcome of allogeneic HCT. Blood. 120(14). 2796–2806. 60 indexed citations

Chien, Jason W., Xinyi Cindy Zhang, Wenhong Fan, et al.. (2012). Evaluation of published single nucleotide polymorphisms associated with acute GVHD. Blood. 119(22). 5311–5319. 72 indexed citations

10.

Méndez, Eduardo, Pawadee Lohavanichbutr, Wenhong Fan, et al.. (2011). Can a Metastatic Gene Expression Profile Outperform Tumor Size as a Predictor of Occult Lymph Node Metastasis in Oral Cancer Patients?. Clinical Cancer Research. 17(8). 2466–2473. 27 indexed citations

11.

Liu, Lei, et al.. (2011). Network user identification based feature weighting naive Bayesian classification algorithm. Journal of Computer Applications. 31(12). 3268–3270. 1 indexed citations

12.

Li, Liang, Min Li, Can‐Lan Sun, et al.. (2011). Altered Hematopoietic Cell Gene Expression Precedes Development of Therapy-Related Myelodysplasia/Acute Myeloid Leukemia and Identifies Patients at Risk. Cancer Cell. 20(5). 591–605. 65 indexed citations

13.

Xu, Chang, Yan Liu, Pei Wang, et al.. (2010). Integrative analysis of DNA copy number and gene expression in metastatic oral squamous cell carcinoma identifies genes associated with poor survival. Molecular Cancer. 9(1). 143–143. 49 indexed citations

14.

Méndez, Eduardo, John R. Houck, David R. Doody, et al.. (2009). A Genetic Expression Profile Associated with Oral Cancer Identifies a Group of Patients at High Risk of Poor Survival. Clinical Cancer Research. 15(4). 1353–1361. 48 indexed citations

15.

Smith, W. P., Quyen Vu, Shuying Sue Li, et al.. (2006). Toward understanding MHC disease associations: Partial resequencing of 46 distinct HLA haplotypes. Genomics. 87(5). 561–571. 56 indexed citations

16.

Guo, Yingying, Linda Breeden, Wenhong Fan, et al.. (2005). Analysis of cellular responses to aflatoxin B1 in yeast expressing human cytochrome P450 1A2 using cDNA microarrays. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 593(1-2). 121–142. 19 indexed citations

17.

Zhao, Lue Ping, et al.. (1999). An efficient, robust and unified method for mapping complex traits (III): Combined linkage/linkage-disequilibrium analysis. American Journal of Medical Genetics. 84(5). 433–453. 6 indexed citations

18.

Lipsitz, Stuart R., Joseph G. Ibrahim, & Lue Ping Zhao. (1999). A Weighted Estimating Equation for Missing Covariate Data with Properties Similar to Maximum Likelihood. Journal of the American Statistical Association. 94(448). 1147–1160. 80 indexed citations

19.

Zhao, Lue Ping, Ross L. Prentice, Fumin Shen, & Li Hsu. (1999). On the Assessment of Statistical Significance in Disease-Gene Discovery. The American Journal of Human Genetics. 64(6). 1739–1753. 8 indexed citations

20.

Zarbl, Helmut, Corinne Aragaki, & Lue Ping Zhao. (1998). An Efficient Protocol for Rare Mutation Genotyping in a Large Population. Genetic Testing. 2(4). 315–321. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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