Ray R. Zhang

904 total citations · 1 hit paper
17 papers, 706 citations indexed

About

Ray R. Zhang is a scholar working on Genetics, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, Ray R. Zhang has authored 17 papers receiving a total of 706 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Genetics, 6 papers in Biomedical Engineering and 5 papers in Molecular Biology. Recurrent topics in Ray R. Zhang's work include Glioma Diagnosis and Treatment (6 papers), Nanoplatforms for cancer theranostics (4 papers) and Medical Imaging Techniques and Applications (3 papers). Ray R. Zhang is often cited by papers focused on Glioma Diagnosis and Treatment (6 papers), Nanoplatforms for cancer theranostics (4 papers) and Medical Imaging Techniques and Applications (3 papers). Ray R. Zhang collaborates with scholars based in United States, Sweden and Taiwan. Ray R. Zhang's co-authors include John S. Kuo, Jamey P. Weichert, Anatoly N. Pinchuk, Joseph J. Grudzinski, Eben L. Rosenthal, Jason M. Warram, Kevin W. Eliceiri, Vladimir Feygelman, Geoffrey Zhang and Paul A. Clark and has published in prestigious journals such as Neurosurgery, Acta Neuropathologica and Nature Reviews Clinical Oncology.

In The Last Decade

Ray R. Zhang

17 papers receiving 697 citations

Hit Papers

Beyond the margins: real-... 2017 2026 2020 2023 2017 100 200 300
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.

  1. Beyond the margins: real-time detection of cancer using targeted fluorophores
    2017 383 citations Ray R. Zhang, Joseph J. Grudzinski et al. Nature Reviews Clinical Oncology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ray R. Zhang United States 11 352 190 160 135 135 17 706
Joseph J. Grudzinski United States 14 329 0.9× 256 1.3× 174 1.1× 348 2.6× 136 1.0× 44 924
Camille Verry France 12 377 1.1× 359 1.9× 87 0.5× 176 1.3× 111 0.8× 36 731
Muhan Liu China 17 358 1.0× 105 0.6× 207 1.3× 234 1.7× 92 0.7× 33 725
Fiona Hegi‐Johnson Australia 11 265 0.8× 373 2.0× 216 1.4× 367 2.7× 82 0.6× 32 1.0k
Brian Madajewski United States 15 509 1.4× 299 1.6× 215 1.3× 180 1.3× 114 0.8× 21 990
Mihaela Ghita United Kingdom 16 146 0.4× 319 1.7× 215 1.3× 293 2.2× 42 0.3× 33 693
Lenka Štefančíková Czechia 13 130 0.4× 225 1.2× 203 1.3× 101 0.7× 66 0.5× 19 484
Melissa S. Germanos United States 3 175 0.5× 110 0.6× 210 1.3× 223 1.7× 46 0.3× 3 600
Eric Blankemeyer United States 10 203 0.6× 72 0.4× 173 1.1× 369 2.7× 64 0.5× 16 814
Mirna El Khatib United States 15 136 0.4× 97 0.5× 127 0.8× 85 0.6× 44 0.3× 26 684

Countries citing papers authored by Ray R. Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Ray R. Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ray R. Zhang. 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 Ray R. Zhang. The network helps show where Ray R. Zhang may publish in the future.

Co-authorship network of co-authors of Ray R. Zhang

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

All Works

17 of 17 papers shown
1.
Zhang, Ray R., Christina L. Brunnquell, Reinier Hernandez, et al.. (2022). Next-Generation Cancer Magnetic Resonance Imaging With Tumor-Targeted Alkylphosphocholine Metal Analogs. Investigative Radiology. 57(10). 655–663. 3 indexed citations
2.
Zhang, Ray R., et al.. (2020). Histological features of gadolinium deposition in the brain, a case report. Acta Neuropathologica. 140(2). 241–244. 2 indexed citations
3.
Zhang, Ray R., Tej I. Mehta, Ronald R. Burnette, et al.. (2019). In Silico Docking of Alkylphosphocholine Analogs to Human Serum Albumin Predicts Partitioning and Pharmacokinetics. Molecular Pharmaceutics. 16(8). 3350–3360. 10 indexed citations
4.
Zhang, Ray R., et al.. (2018). Zika Virus has Oncolytic Activity Against Glioblastoma Stem Cells. Neurosurgery. 82(5). E113–E114. 35 indexed citations
5.
Zhang, Ray R., et al.. (2018). Extracellular Vesicles Containing PD-L1 Contribute to Immune Evasion in Glioblastoma. Neurosurgery. 83(3). E98–E100. 11 indexed citations
6.
Zhang, Ray R., Joseph J. Grudzinski, Eben L. Rosenthal, et al.. (2017). Beyond the margins: real-time detection of cancer using targeted fluorophores. Nature Reviews Clinical Oncology. 14(6). 347–364. 383 indexed citations breakdown →
7.
8.
Zhang, Ray R. & John S. Kuo. (2016). Detection of Human Brain Tumor Infiltration With Quantitative Stimulated Raman Scattering Microscopy. Neurosurgery. 78(4). N9–N11. 12 indexed citations
9.
10.
Zhang, Ray R., Kyle I. Swanson, Lance T. Hall, Jamey P. Weichert, & John S. Kuo. (2016). Diapeutic cancer-targeting alkylphosphocholine analogs may advance management of brain malignancies. CNS Oncology. 5(4). 223–231. 16 indexed citations
11.
Clark, Paul A., Abraham Al‐Ahmad, Tongcheng Qian, et al.. (2016). Analysis of Cancer-Targeting Alkylphosphocholine Analogue Permeability Characteristics Using a Human Induced Pluripotent Stem Cell Blood–Brain Barrier Model. Molecular Pharmaceutics. 13(9). 3341–3349. 31 indexed citations
12.
Zhang, Ray R., Kelli B. Pointer, & John S. Kuo. (2015). New Molecular Insights and Potential Therapies for Diffuse Intrinsic Pontine Glioma. Neurosurgery. 77(4). N13–N14. 1 indexed citations
13.
Swanson, Kyle I., Paul A. Clark, Ray R. Zhang, et al.. (2014). Fluorescent Cancer-Selective Alkylphosphocholine Analogs for Intraoperative Glioma Detection. Neurosurgery. 76(2). 115–124. 57 indexed citations
14.
Feygelman, Vladimir, Ray R. Zhang, Eduardo G. Moros, et al.. (2014). Monte Carlo comparison of superficial dose between flattening filter free and flattened beams. Physica Medica. 30(4). 503–508. 28 indexed citations
15.
Zhang, Ray R., Kelli B. Pointer, John S. Kuo, & Robert J. Dempsey. (2014). Mutational Analysis Reveals the Origin and Therapy-Driven Evolution of Recurrent Glioma. Neurosurgery. 75(6). N9–N10. 27 indexed citations
16.
Zhang, Ray R., Vladimir Feygelman, Eleanor Harris, et al.. (2013). Is wax equivalent to tissue in electron conformal therapy planning? A Monte Carlo study of material approximation introduced dose difference. Journal of Applied Clinical Medical Physics. 14(1). 92–101. 7 indexed citations
17.

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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