Bingbing Dai

3.9k total citations
48 papers, 2.3k citations indexed

About

Bingbing Dai is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Bingbing Dai has authored 48 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 11 papers in Oncology and 9 papers in Immunology. Recurrent topics in Bingbing Dai's work include FOXO transcription factor regulation (7 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Cancer Mechanisms and Therapy (5 papers). Bingbing Dai is often cited by papers focused on FOXO transcription factor regulation (7 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Cancer Mechanisms and Therapy (5 papers). Bingbing Dai collaborates with scholars based in United States, China and United Kingdom. Bingbing Dai's co-authors include Suyun Huang, Raymond Sawaya, Keping Xie, Kenneth Aldape, Mingguang Liu, Bingliang Fang, John D. Minna, Nu Zhang, Jack A. Roth and Jason B. Fleming and has published in prestigious journals such as Journal of Biological Chemistry, Gastroenterology and PLoS ONE.

In The Last Decade

Bingbing Dai

43 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bingbing Dai United States 28 1.6k 590 470 342 269 48 2.3k
José M.A. Moreira Denmark 31 1.8k 1.2× 656 1.1× 670 1.4× 176 0.5× 239 0.9× 79 2.8k
Jérôme Tamburini France 31 2.2k 1.4× 540 0.9× 446 0.9× 373 1.1× 359 1.3× 88 3.3k
Joan Montero Spain 20 1.4k 0.9× 657 1.1× 387 0.8× 233 0.7× 284 1.1× 43 2.3k
Juha Klefström Finland 23 1.3k 0.8× 756 1.3× 423 0.9× 254 0.7× 218 0.8× 55 2.1k
Katherine M. Aird United States 29 2.1k 1.3× 659 1.1× 658 1.4× 314 0.9× 406 1.5× 58 3.0k
Xin Xu China 26 1.4k 0.9× 758 1.3× 709 1.5× 177 0.5× 222 0.8× 84 2.3k
Pietro Taverna United States 27 1.8k 1.1× 788 1.3× 359 0.8× 455 1.3× 286 1.1× 90 2.5k
Antonella Papa United States 18 2.4k 1.5× 855 1.4× 560 1.2× 296 0.9× 247 0.9× 29 3.1k
Sohye Kang United States 16 1.9k 1.2× 695 1.2× 353 0.8× 300 0.9× 175 0.7× 18 2.4k
Runzhou Ni China 29 1.8k 1.1× 436 0.7× 711 1.5× 151 0.4× 417 1.6× 103 2.4k

Countries citing papers authored by Bingbing Dai

Since Specialization
Citations

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

Fields of papers citing papers by Bingbing Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bingbing Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Bingbing Dai. A scholar is included among the top collaborators of Bingbing Dai 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 Bingbing Dai. Bingbing Dai 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.
2.
Zhang, Yali, et al.. (2023). What affects the accuracy and applicability of determining wastewater sludge water content via low-field nuclear magnetic resonance?. Environmental Research. 226. 115702–115702. 4 indexed citations
3.
Liu, Huiyuan, Jiaming Cao, Jiahui Li, et al.. (2023). Sema4D as a biomarker for Predicting rheumatoid arthritis disease activity. Clinical Rheumatology. 43(2). 645–655.
4.
Liang, Yan, Bo Tu, Jun Yao, et al.. (2021). Targeting Glucose Metabolism Sensitizes Pancreatic Cancer to MEK Inhibition. Cancer Research. 81(15). 4054–4065. 30 indexed citations
5.
Deng, Jenying, Ya’an Kang, Xinqun Li, et al.. (2021). DDR1-induced neutrophil extracellular traps drive pancreatic cancer metastasis. JCI Insight. 6(17). 89 indexed citations
6.
Dai, Bingbing, Jithesh J. Augustine, Ya’an Kang, et al.. (2021). Compound NSC84167 selectively targets NRF2-activated pancreatic cancer by inhibiting asparagine synthesis pathway. Cell Death and Disease. 12(7). 693–693. 7 indexed citations
7.
Dai, Bingbing, David Roife, Ya’an Kang, et al.. (2017). Preclinical Evaluation of Sequential Combination of Oncolytic Adenovirus Delta-24-RGD and Phosphatidylserine-Targeting Antibody in Pancreatic Ductal Adenocarcinoma. Molecular Cancer Therapeutics. 16(4). 662–670. 17 indexed citations
8.
Kang, Ya’an, David Roife, Michael Pratt, et al.. (2017). Prolonged exposure to extracellular lumican restrains pancreatic adenocarcinoma growth. Oncogene. 36(38). 5432–5438. 35 indexed citations
9.
Kang, Ya’an, David Roife, Yeon‐Ju Lee, et al.. (2016). Transforming Growth Factor-β Limits Secretion of Lumican by Activated Stellate Cells within Primary Pancreatic Adenocarcinoma Tumors. Clinical Cancer Research. 22(19). 4934–4946. 29 indexed citations
10.
Roife, David, Bingbing Dai, Ya’an Kang, et al.. (2016). Ex Vivo Testing of Patient-Derived Xenografts Mirrors the Clinical Outcome of Patients with Pancreatic Ductal Adenocarcinoma. Clinical Cancer Research. 22(24). 6021–6030. 46 indexed citations
11.
Dai, Bingbing, et al.. (2015). Regression of Stage IV Pancreatic Cancer to Curative Surgery and Introduction of a Novel Ex-Vivo Chemosensitivity Assay. Cureus. 7(12). e423–e423. 4 indexed citations
12.
Dai, Bingbing, Suk-Young Yoo, Geoffrey Bartholomeusz, et al.. (2013). KEAP1-Dependent Synthetic Lethality Induced by AKT and TXNRD1 Inhibitors in Lung Cancer. Cancer Research. 73(17). 5532–5543. 55 indexed citations
13.
Lu, Haibo, Li Wang, Wen Gao, et al.. (2013). IGFBP2/FAK Pathway Is Causally Associated with Dasatinib Resistance in Non–Small Cell Lung Cancer Cells. Molecular Cancer Therapeutics. 12(12). 2864–2873. 52 indexed citations
14.
Dai, Bingbing, Jieru Meng, Michael Peyton, et al.. (2011). STAT3 Mediates Resistance to MEK Inhibitor through MicroRNA miR-17. Cancer Research. 71(10). 3658–3668. 80 indexed citations
15.
Li, Qiang, Nu Zhang, Zhiliang Jia, et al.. (2009). Critical Role and Regulation of Transcription Factor FoxM1 in Human Gastric Cancer Angiogenesis and Progression. Cancer Research. 69(8). 3501–3509. 177 indexed citations
16.
Meng, Jieru, Bingbing Dai, Wei Guo, et al.. (2009). High level of AKT activity is associated with resistance to MEK inhibitor AZD6244 (ARRY-142886). Cancer Biology & Therapy. 8(21). 2073–2080. 51 indexed citations
17.
Cai, Rong, et al.. (2009). SATB1 binds an intronic MAR sequence in human PI3kγ in vitro. Molecular Biology Reports. 37(3). 1461–1465. 3 indexed citations
18.
Zhang, Yujian, Nu Zhang, Bingbing Dai, et al.. (2008). FoxM1B Transcriptionally Regulates Vascular Endothelial Growth Factor Expression and Promotes the Angiogenesis and Growth of Glioma Cells. Cancer Research. 68(21). 8733–8742. 164 indexed citations
19.
Li, Kai, Rong Cai, Bingbing Dai, et al.. (2007). SATB1 regulates SPARC expression in K562 cell line through binding to a specific sequence in the third intron. Biochemical and Biophysical Research Communications. 356(1). 6–12. 16 indexed citations
20.
Dai, Bingbing, Ying Lei, Rong Cai, et al.. (2006). Identification of a nuclear matrix attachment region like sequence in the last intron of PI3Kγ. Biochemical and Biophysical Research Communications. 341(2). 583–590. 6 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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