Fu Su

470 total citations
8 papers, 390 citations indexed

About

Fu Su is a scholar working on Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Fu Su has authored 8 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Oncology, 3 papers in Molecular Biology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Fu Su's work include Lymphatic System and Diseases (3 papers), Angiogenesis and VEGF in Cancer (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). Fu Su is often cited by papers focused on Lymphatic System and Diseases (3 papers), Angiogenesis and VEGF in Cancer (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). Fu Su collaborates with scholars based in China, United States and Switzerland. Fu Su's co-authors include Paul L. Beaumier, Donald B. Axworthy, Alan R. Fritzberg, J. M. Reno, Robert W. Mallett, Mark D. Hylarides, Louis Theodore, Paul L. Weiden, John M. Reno and Scott S. Graves and has published in prestigious journals such as Proceedings of the National Academy of Sciences, International Journal of Oncology and Journal of drug targeting.

In The Last Decade

Fu Su

8 papers receiving 375 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fu Su China	7	281	95	82	74	50	8	390
Don K. Hamlin United States	8	322 1.1×	65 0.7×	69 0.8×	122 1.6×	37 0.7×	12	402
Don B. Axworthy United States	11	524 1.9×	83 0.9×	134 1.6×	204 2.8×	58 1.2×	14	634
Warak Chaovapong United States	7	310 1.1×	112 1.2×	122 1.5×	36 0.5×	41 0.8×	10	405
Christine Grinnell United States	8	302 1.1×	295 3.1×	99 1.2×	39 0.5×	18 0.4×	12	490
Kelly Davis Orcutt United States	13	334 1.2×	201 2.1×	155 1.9×	32 0.4×	23 0.5×	25	510
Josefa Chuh United States	7	247 0.9×	138 1.5×	263 3.2×	21 0.3×	23 0.5×	9	397
Zi-Fen Su Canada	8	192 0.7×	88 0.9×	104 1.3×	13 0.2×	12 0.2×	15	349
Kevin L. Alston United States	11	341 1.2×	76 0.8×	122 1.5×	6 0.1×	36 0.7×	12	412
Tal Flieswasser Belgium	9	84 0.3×	171 1.8×	232 2.8×	27 0.4×	14 0.3×	10	508
Leanne Lanieri United States	7	137 0.5×	86 0.9×	179 2.2×	43 0.6×	29 0.6×	17	286

Countries citing papers authored by Fu Su

Since Specialization

Citations

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

Fields of papers citing papers by Fu Su

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fu Su

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

All Works

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8 of 8 papers shown

Hou, Zhenyu, Qiang Wang, Zhide Guo, et al.. (2019). Gadolinium-conjugated CB86: a novel TSPO-targeting MRI contrast agent for imaging of rheumatoid arthritis. Journal of drug targeting. 28(4). 398–407. 12 indexed citations

Ma, Chao, Xiaofeng Dou, Jianghua Yan, et al.. (2019). Optimal Saturated Neuropilin-1 Expression in Normal Tissue Maximizes Tumor Exposure to Anti-Neuropilin-1 Monoclonal Antibody. Anti-Cancer Agents in Medicinal Chemistry. 19(18). 2269–2275. 2 indexed citations

Chen, Li-Chun, Liangliang Wang, Jianghua Yan, et al.. (2016). 131I-labeled monoclonal antibody targeting neuropilin receptor type-2 for tumor SPECT imaging. International Journal of Oncology. 50(2). 649–659. 9 indexed citations

Zhang, Yafei, Peng Liu, Xiaofeng Dou, et al.. (2015). High Expression of Neuropilin-1 Associates with Unfavorable Clinicopathological Features in Hepatocellular Carcinoma. Pathology & Oncology Research. 22(2). 367–375. 25 indexed citations

Su, Xinhui, Qilin Ma, Guibing Chen, et al.. (2015). Effect of local mild hypothermia on regional cerebral blood flow in patients with acute intracerebral hemorrhage assessed by ^{99m}Tc-ECD SPECT imaging. Journal of X-Ray Science and Technology. 23(1). 101–109. 13 indexed citations

Breitz, Hazel B., Paul L. Weiden, Paul L. Beaumier, et al.. (2000). Clinical optimization of pretargeted radioimmunotherapy with antibody-streptavidin conjugate and 90Y-DOTA-biotin.. PubMed. 41(1). 131–40. 124 indexed citations

Axworthy, Donald B., J. M. Reno, Mark D. Hylarides, et al.. (2000). Cure of human carcinoma xenografts by a single dose of pretargeted yttrium-90 with negligible toxicity. Proceedings of the National Academy of Sciences. 97(4). 1802–1807. 190 indexed citations

Kotts, Claire E., Fu Su, Tom Dodd, et al.. (1996). ¹⁸⁶ Re-Labeled Antibodies to p185 ^HER2 as HER2-Targeted Radioimmunopharmaceutical Agents: Comparison of Physical and Biological Characteristics with ¹²⁵ I and ¹³¹ I-Labeled Counterparts. Cancer Biotherapy and Radiopharmaceuticals. 11(2). 133–144. 15 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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