Bo Tang

1.6k total citations · 1 hit paper
58 papers, 1.1k citations indexed

About

Bo Tang is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Bo Tang has authored 58 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 22 papers in Oncology and 12 papers in Immunology. Recurrent topics in Bo Tang's work include Colorectal Cancer Surgical Treatments (8 papers), Colorectal Cancer Screening and Detection (5 papers) and Cell death mechanisms and regulation (5 papers). Bo Tang is often cited by papers focused on Colorectal Cancer Surgical Treatments (8 papers), Colorectal Cancer Screening and Detection (5 papers) and Cell death mechanisms and regulation (5 papers). Bo Tang collaborates with scholars based in China, United States and Macao. Bo Tang's co-authors include Xiang‐Xi Xu, J. David Lambeth, Taolin Yi, Taiyuan Li, Luhua Lai, Xiong Lei, Yifei Qi, Qian Wang, Martin Sonenberg and Wu Yin and has published in prestigious journals such as Journal of Biological Chemistry, Angewandte Chemie International Edition and SHILAP Revista de lepidopterología.

In The Last Decade

Bo Tang

54 papers receiving 1.1k citations

Hit Papers

Robotic versus laparoscopic surgery for middle and low re... 2022 2026 2023 2024 2022 50 100 150 200
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. Robotic versus laparoscopic surgery for middle and low rectal cancer (REAL): short-term outcomes of a multicentre randomised controlled trial
    2022 237 citations Taiyuan Li, Bo Tang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bo Tang China 18 522 451 313 168 116 58 1.1k
Justyna Mikuła‐Pietrasik Poland 23 547 1.0× 359 0.8× 245 0.8× 212 1.3× 212 1.8× 62 1.4k
Christian Mayr Austria 20 632 1.2× 305 0.7× 204 0.7× 222 1.3× 91 0.8× 58 1.1k
Pawan Noel United States 15 432 0.8× 371 0.8× 307 1.0× 149 0.9× 111 1.0× 25 943
Kai Lee Yap United States 17 481 0.9× 306 0.7× 195 0.6× 203 1.2× 176 1.5× 42 1.0k
Megumi Baba Japan 19 395 0.8× 294 0.7× 167 0.5× 224 1.3× 89 0.8× 48 977
Sang‐Hyun Song South Korea 26 938 1.8× 382 0.8× 330 1.1× 187 1.1× 87 0.8× 79 1.7k
Jin-Woo Kim South Korea 13 508 1.0× 256 0.6× 155 0.5× 272 1.6× 95 0.8× 40 1.1k
Cuiling Qi China 19 545 1.0× 346 0.8× 100 0.3× 296 1.8× 163 1.4× 44 1.1k
Yuanfeng Gong China 18 475 0.9× 317 0.7× 223 0.7× 321 1.9× 66 0.6× 50 1.0k
Lantu Gou China 20 547 1.0× 403 0.9× 93 0.3× 138 0.8× 160 1.4× 56 1.1k

Countries citing papers authored by Bo Tang

Since Specialization
Citations

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

Fields of papers citing papers by Bo Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bo Tang

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

All Works

20 of 20 papers shown
1.
Zhang, Jingjing, et al.. (2025). TLR4al senses heme as a key damage/danger-associated molecular pattern to activate immune responses in lower vertebrates. The Journal of Immunology. 214(11). 3083–3099. 1 indexed citations
2.
3.
Tang, Bo, Mengxing Guo, Yujia Zhai, et al.. (2024). Human esophageal cancer stem-like cells escape the cytotoxicity of natural killer cells via down-regulation of ULBP-1. Journal of Translational Medicine. 22(1). 737–737. 3 indexed citations
4.
Yang, Xiaodi, Qingyun Wang, Bo Tang, et al.. (2024). Comparative analysis of dynamic transcriptomes reveals specific COVID-19 features and pathogenesis of immunocompromised populations. mSystems. 9(6). e0138523–e0138523. 1 indexed citations
5.
Wu, Chuanchen, Yuantao Mao, Fanghui Zhang, et al.. (2023). Uncovering the mechanism of cancer-associated fibroblasts induced immune evasion of hepatocellular carcinoma cells via in situ fluorescence imaging. Sensors and Actuators B Chemical. 389. 133891–133891. 8 indexed citations
6.
Tang, Bo, Tao Li, Tao Li, et al.. (2022). Learning Curve of Robotic-Assisted Total Mesorectal Excision for Rectal Cancer. Frontiers in Oncology. 12. 931426–931426. 13 indexed citations
7.
Liu, Weishuai, Xiaozhou Yu, Yixing Feng, et al.. (2022). CD73, a Promising Therapeutic Target of Diclofenac, Promotes Metastasis of Pancreatic Cancer through a Nucleotidase Independent Mechanism. Advanced Science. 10(6). e2206335–e2206335. 22 indexed citations
8.
Zhao, Liang, Min Soo Kang, Xiaomeng Liu, et al.. (2022). UBR7 inhibits HCC tumorigenesis by targeting Keap1/Nrf2/Bach1/HK2 and glycolysis. Journal of Experimental & Clinical Cancer Research. 41(1). 330–330. 48 indexed citations
9.
10.
Tang, Bo, Dongning Liu, Qunguang Jiang, et al.. (2022). Male urogenital function after robot-assisted and laparoscopic total mesorectal excision for rectal cancer: a prospective cohort study. BMC Surgery. 22(1). 185–185. 8 indexed citations
11.
12.
Zhou, A., Liu H, & Bo Tang. (2020). Comprehensive Evaluation of Endocytosis-Associated Protein SCAMP3 in Hepatocellular Carcinoma. SHILAP Revista de lepidopterología. 2 indexed citations
13.
Zhu, Weiquan, Dongning Liu, Xiong Lei, et al.. (2020). Robotic- vs laparoscopic-assisted proctectomy for locally advanced rectal cancer based on propensity score matching: Short-term outcomes at a colorectal center in China. World Journal of Gastrointestinal Oncology. 12(4). 424–434. 13 indexed citations
14.
Wei, Dong, et al.. (2020). Downregulation of CDCA3 expression inhibits tumor formation in pancreatic cancer. Neoplasma. 67(6). 1223–1232. 12 indexed citations
15.
16.
Zhang, Changsheng, Qi Shen, Bo Tang, & Luhua Lai. (2013). Computational Design of Helical Peptides Targeting TNFα. Angewandte Chemie. 125(42). 11265–11268. 2 indexed citations
17.
Zhou, Jiahua, et al.. (2007). hTERT-targeted E. coli purine nucleoside phosphorylase gene/6-methylpurine deoxyribose therapy for pancreatic cancer. Chinese Medical Journal. 120(15). 1348–1352. 18 indexed citations
18.
Tang, Bo, et al.. (2005). Fast and sensitive spectrofluorimetric determination of trace amount of Pb(II) in sludge using o-vanillin-8-aminoquinoline. Chemia Analityczna. 50(3). 631–639. 1 indexed citations
19.
Xu, Xiang‐Xi, Taolin Yi, Bo Tang, & J. David Lambeth. (1998). Disabled-2 (Dab2) is an SH3 domain-binding partner of Grb2. Oncogene. 16(12). 1561–1569. 105 indexed citations
20.
Tang, Bo, et al.. (1995). Mitogenic Response to TGF-β in 3T3-F442A Cells. Biochemical and Biophysical Research Communications. 216(3). 964–969. 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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