Shou Ching Tang

1.7k total citations
7 papers, 506 citations indexed

About

Shou Ching Tang is a scholar working on Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shou Ching Tang has authored 7 papers receiving a total of 506 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Oncology, 3 papers in Molecular Biology and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shou Ching Tang's work include Monoclonal and Polyclonal Antibodies Research (3 papers), Glycosylation and Glycoproteins Research (1 paper) and Cell death mechanisms and regulation (1 paper). Shou Ching Tang is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (3 papers), Glycosylation and Glycoproteins Research (1 paper) and Cell death mechanisms and regulation (1 paper). Shou Ching Tang collaborates with scholars based in Canada, China and United States. Shou Ching Tang's co-authors include Andrew Shaw, Joseph R. Slupsky, Jutta Seehafer, Badi El Osta, Fangyuan Hu, A Masellis-Smith, Sean Dolan, Susan Burdette-Radoux, Marna B. McKenzie and Félix Couture and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Critical Reviews in Oncology/Hematology.

In The Last Decade

Shou Ching Tang

6 papers receiving 491 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shou Ching Tang Canada	6	200	177	103	100	99	7	506
GL Rosner United States	6	292 1.5×	344 1.9×	134 1.3×	128 1.3×	43 0.4×	7	605
JF DiPersio United States	14	219 1.1×	174 1.0×	302 2.9×	138 1.4×	53 0.5×	24	651
Masaharu Nobuyoshi Japan	13	307 1.5×	384 2.2×	82 0.8×	424 4.2×	72 0.7×	22	720
John D. Iuliucci United States	13	212 1.1×	122 0.7×	95 0.9×	316 3.2×	28 0.3×	16	637
John Hewson Australia	13	168 0.8×	285 1.6×	154 1.5×	265 2.6×	33 0.3×	19	638
Shaivy Malik India	12	277 1.4×	88 0.5×	251 2.4×	152 1.5×	37 0.4×	31	563
Hironobu Shibata Japan	11	440 2.2×	445 2.5×	103 1.0×	342 3.4×	30 0.3×	41	764
Birgit K. Kramp Germany	7	216 1.1×	125 0.7×	324 3.1×	153 1.5×	87 0.9×	7	569
Abdo Abou-Slaybi United States	3	181 0.9×	138 0.8×	61 0.6×	174 1.7×	21 0.2×	6	423
Christopher B. Hopson United States	8	53 0.3×	370 2.1×	64 0.6×	109 1.1×	22 0.2×	13	514

Countries citing papers authored by Shou Ching Tang

Since Specialization

Citations

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

Fields of papers citing papers by Shou Ching Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shou Ching Tang. 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 Shou Ching Tang. The network helps show where Shou Ching Tang may publish in the future.

Co-authorship network of co-authors of Shou Ching Tang

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

All Works

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7 of 7 papers shown

Osta, Badi El, et al.. (2017). Not all immune-checkpoint inhibitors are created equal: Meta-analysis and systematic review of immune-related adverse events in cancer trials. Critical Reviews in Oncology/Hematology. 119. 1–12. 146 indexed citations

Tang, Shou Ching, et al.. (2016). Chemotherapy for Breast Cancer During Pregnancy, With Neonatal Lupus in the Newborn.. PubMed. 30(6). 584–7.

Quirt, Ian, Catherine Y. Lau, M.J. Kovacs, et al.. (2001). Epoetin Alfa Therapy Increases Hemoglobin Levels and Improves Quality of Life in Patients With Cancer-Related Anemia Who Are Not Receiving Chemotherapy and Patients With Anemia Who Are Receiving Chemotherapy. Journal of Clinical Oncology. 19(21). 4126–4134. 121 indexed citations

Yang, Xiaolong, Y Hao, Zhaobing Ding, Alan Pater, & Shou Ching Tang. (1999). Differential expression of antiapoptotic gene BAG-1 in human breast normal and cancer cell lines and tissues.. PubMed. 5(7). 1816–22. 41 indexed citations

Tang, Shou Ching, et al.. (1996). Immunosuppressive Toxicity of CAMPATH®1H Monoclonal Antibody in the Treatment of Patients with Recurrent Low Grade Lymphoma. Leukemia & lymphoma. 24(1-2). 93–101. 45 indexed citations

Slupsky, Joseph R., Jutta Seehafer, Shou Ching Tang, A Masellis-Smith, & Andrew Shaw. (1989). Evidence That Monoclonal Antibodies against CD9 Antigen Induce Specific Association between CD9 and the Platelet Glycoprotein IIb-IIIa Complex. Journal of Biological Chemistry. 264(21). 12289–12293. 128 indexed citations

Seehafer, Jutta, Shou Ching Tang, Joseph R. Slupsky, & Andrew Shaw. (1988). The functional glycoprotein CD9 is variably acylated: localization of the variably acylated region to a membrane-associated peptide containing the binding site for the agonistic monoclonal antibody 50H.19. Biochimica et Biophysica Acta (BBA) - Protein Structure and Molecular Enzymology. 957(3). 399–410. 25 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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