Jiabu Ye

558 total citations
19 papers, 339 citations indexed

About

Jiabu Ye is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Jiabu Ye has authored 19 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 9 papers in Pulmonary and Respiratory Medicine and 6 papers in Cancer Research. Recurrent topics in Jiabu Ye's work include Cancer Immunotherapy and Biomarkers (11 papers), Lung Cancer Treatments and Mutations (7 papers) and Cancer Genomics and Diagnostics (6 papers). Jiabu Ye is often cited by papers focused on Cancer Immunotherapy and Biomarkers (11 papers), Lung Cancer Treatments and Mutations (7 papers) and Cancer Genomics and Diagnostics (6 papers). Jiabu Ye collaborates with scholars based in United States, United Kingdom and Japan. Jiabu Ye's co-authors include Pralay Mukhopadhyay, Satrajit Roychoudhury, Keaven M. Anderson, Brandon W. Higgs, Naiyer A. Rizvi, Han Si, Michael Kuziora, Koustubh Ranade, Solange Peters and Urban Scheuring and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Jiabu Ye

18 papers receiving 336 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiabu Ye United States 9 226 162 110 51 34 19 339
Kaitlyn R. Antonelli United States 7 225 1.0× 137 0.8× 140 1.3× 18 0.4× 71 2.1× 10 309
Andrew L. Rygiel United States 8 251 1.1× 151 0.9× 159 1.4× 26 0.5× 82 2.4× 12 332
Amy Gravell United States 6 151 0.7× 66 0.4× 82 0.7× 39 0.8× 90 2.6× 10 302
O. Rixe France 8 355 1.6× 128 0.8× 170 1.5× 19 0.4× 89 2.6× 16 482
Eduardo J. Pennella United States 11 416 1.8× 377 2.3× 62 0.6× 14 0.3× 82 2.4× 33 578
M. Savina France 7 149 0.7× 200 1.2× 26 0.2× 15 0.3× 21 0.6× 10 275
J. Subramanian United States 4 90 0.4× 168 1.0× 148 1.3× 40 0.8× 201 5.9× 6 429
Marie Hjälm-Eriksson Sweden 8 113 0.5× 367 2.3× 111 1.0× 30 0.6× 87 2.6× 17 455
Elisa Rizzo Italy 6 190 0.8× 132 0.8× 76 0.7× 97 1.9× 47 1.4× 7 343
Anwar M. Hossain United States 12 146 0.6× 114 0.7× 21 0.2× 85 1.7× 50 1.5× 18 329

Countries citing papers authored by Jiabu Ye

Since Specialization
Citations

This map shows the geographic impact of Jiabu Ye'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 Jiabu Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiabu Ye more than expected).

Fields of papers citing papers by Jiabu Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiabu Ye. 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 Jiabu Ye. The network helps show where Jiabu Ye may publish in the future.

Co-authorship network of co-authors of Jiabu Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Jiabu Ye. A scholar is included among the top collaborators of Jiabu Ye 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 Jiabu Ye. Jiabu Ye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Lin, Ray, Pralay Mukhopadhyay, Satrajit Roychoudhury, et al.. (2023). Comment on “Non-Proportional Hazards – an Evaluation of the MaxCombo Test in Cancer Clinical Trials” by the Cross-Pharma Non-Proportional Hazards Working Group. Statistics in Biopharmaceutical Research. 15(2). 312–314. 1 indexed citations
2.
Wildsmith, Sophie, Jiabu Ye, Giovanni Melillo, et al.. (2022). Association of PD-L1 Expression on Tumor and Immune Cells with Survival in Recurrent or Metastatic Head and Neck Squamous Cell Carcinoma and Assay Validation. Cancer Research Communications. 2(1). 39–48. 7 indexed citations
3.
Ye, Jiabu & Dejian Lai. (2022). Empirical Power and Type I Error of Covariate Adjusted Nonparametric Methods. Mathematics and Statistics. 10(5). 1050–1074.
4.
Ye, Jiabu, Dejian Lai, Lemuel A. Moyé, & Barry R. Davis. (2022). Applications of covariate adjusted nonparametric methods to CCTRN clinical trials. PubMed. 8(4). 728–737. 1 indexed citations
5.
Mukhopadhyay, Pralay, Jiabu Ye, Keaven M. Anderson, et al.. (2022). Log-Rank Test vs MaxCombo and Difference in Restricted Mean Survival Time Tests for Comparing Survival Under Nonproportional Hazards in Immuno-oncology Trials. JAMA Oncology. 8(9). 1294–1294. 23 indexed citations
6.
Shameer, Khader, Youyi Zhang, Dan Jackson, et al.. (2021). Correlation Between Early Endpoints and Overall Survival in Non-Small-Cell Lung Cancer: A Trial-Level Meta-Analysis. Frontiers in Oncology. 11. 672916–672916. 17 indexed citations
7.
Roychoudhury, Satrajit, Keaven M. Anderson, Jiabu Ye, & Pralay Mukhopadhyay. (2021). Robust Design and Analysis of Clinical Trials With Nonproportional Hazards: A Straw Man Guidance From a Cross-Pharma Working Group. Statistics in Biopharmaceutical Research. 15(2). 280–294. 35 indexed citations
8.
Si, Han, Michael Kuziora, Katie Quinn, et al.. (2020). A Blood-based Assay for Assessment of Tumor Mutational Burden in First-line Metastatic NSCLC Treatment: Results from the MYSTIC Study. Clinical Cancer Research. 27(6). 1631–1640. 86 indexed citations
9.
Zając, M, Jiabu Ye, Pralay Mukhopadhyay, et al.. (2020). Optimal PD-L1–high cutoff for association with overall survival in patients with urothelial cancer treated with durvalumab monotherapy. PLoS ONE. 15(4). e0231936–e0231936. 16 indexed citations
10.
Rao, Ganesh, Adrian Harvey, Fassil B. Mesfin, et al.. (2020). Temporal Change in Tumor Volume Following Stereotactic Radiosurgery to a Single Brain Metastasis. World Neurosurgery. 136. e328–e333. 3 indexed citations
13.
Ye, Jiabu & Dejian Lai. (2020). Estimations of treatment effects based on covariate adjusted nonparametric methods. SHILAP Revista de lepidopterología. 7(1). 1750878–1750878. 2 indexed citations
14.
Rizvi, Naiyer A., Byoung Chul Cho, Niels Reinmuth, et al.. (2019). OA04.07 Mutations Associated with Sensitivity or Resistance to Immunotherapy in mNSCLC: Analysis from the MYSTIC Trial. Journal of Thoracic Oncology. 14(10). S217–S217. 43 indexed citations
15.
Sridhar, Sriram, Luis Paz‐Ares, Hao Liu, et al.. (2019). Prognostic Significance of Liver Metastasis in Durvalumab-Treated Lung Cancer Patients. Clinical Lung Cancer. 20(6). e601–e608. 37 indexed citations
17.
Si, Han, Brandon W. Higgs, Philip Z. Brohawn, et al.. (2018). Somatic mutations in BRCA2, NFE2L2, ARID1A and NOTCH1 sensitize to anti-PDL1 therapy in multiple tumor types. Annals of Oncology. 29. x1–x1. 4 indexed citations
18.
Ye, Jiabu, Pralay Mukhopadhyay, Xiaoping Jin, et al.. (2018). Optimization of PD-L1 algorithm for predicting overall survival (OS) in patients with urothelial cancer (UC) treated with durvalumab monotherapy.. Journal of Clinical Oncology. 36(15_suppl). 4530–4530. 1 indexed citations
19.
Walker, Jill, Jiabu Ye, Marietta Scott, et al.. (2018). Impact of different programmed cell death ligand-1 (PD-L1) expression algorithms on patient selection and durvalumab efficacy in urothelial carcinoma (UC). Annals of Oncology. 29. viii322–viii322. 2 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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