Carol Tang

2.0k total citations
44 papers, 1.4k citations indexed

About

Carol Tang is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Carol Tang has authored 44 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 17 papers in Genetics and 11 papers in Oncology. Recurrent topics in Carol Tang's work include Glioma Diagnosis and Treatment (17 papers), Cancer Cells and Metastasis (9 papers) and MicroRNA in disease regulation (4 papers). Carol Tang is often cited by papers focused on Glioma Diagnosis and Treatment (17 papers), Cancer Cells and Metastasis (9 papers) and MicroRNA in disease regulation (4 papers). Carol Tang collaborates with scholars based in Singapore, United States and France. Carol Tang's co-authors include Beng Ti Ang, Shazib Pervaiz, Beng-Ti Ang, Edwin Sandanaraj, Yuk Kien Chong, Steven I. Reed, Dang Hoang Lam, Yukti Choudhury, Shu Wang and Felix Chang Tay and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Carol Tang

44 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Carol Tang Singapore 22 908 367 355 216 210 44 1.4k
Carsten Hagemann Germany 26 1.1k 1.2× 419 1.1× 404 1.1× 184 0.9× 320 1.5× 74 2.0k
Jennifer R. Molina United States 13 813 0.9× 313 0.9× 400 1.1× 196 0.9× 114 0.5× 21 1.6k
Joseph Negri United States 21 933 1.0× 219 0.6× 613 1.7× 164 0.8× 81 0.4× 47 1.6k
Ana C. deCarvalho United States 25 1.1k 1.2× 698 1.9× 456 1.3× 199 0.9× 481 2.3× 44 2.0k
Andrei M. Mikheev United States 21 693 0.8× 273 0.7× 427 1.2× 68 0.3× 220 1.0× 39 1.6k
Brian A. Joughin United States 23 1.2k 1.3× 251 0.7× 357 1.0× 267 1.2× 73 0.3× 40 1.7k
Amanda Linkous United States 14 525 0.6× 200 0.5× 247 0.7× 85 0.4× 263 1.3× 22 886
Nagi G. Ayad United States 20 1.7k 1.9× 321 0.9× 430 1.2× 466 2.2× 229 1.1× 59 2.2k
Fumiharu Ohka Japan 23 1.0k 1.1× 678 1.8× 309 0.9× 71 0.3× 525 2.5× 99 1.8k

Countries citing papers authored by Carol Tang

Since Specialization
Citations

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

Fields of papers citing papers by Carol Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carol Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Carol Tang. A scholar is included among the top collaborators of Carol 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 Carol Tang. Carol 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.
Wu, Xingjie, Xuecheng Sun, Auginia Natalia, et al.. (2024). Magnetic augmentation through multi-gradient coupling enables direct and programmable profiling of circulating biomarkers. Nature Communications. 15(1). 8410–8410. 5 indexed citations
2.
3.
Zhang, Yan, Carine Z. J. Lim, Qingchang Chen, et al.. (2023). Multiplexed RNA profiling by regenerative catalysis enables blood-based subtyping of brain tumors. Nature Communications. 14(1). 4278–4278. 28 indexed citations
4.
Novera, Wisna, See Wee Lim, Yuk Kien Chong, et al.. (2022). Integrative multi-omics approach to targeted therapy for glioblastoma. Pharmacological Research. 182. 106308–106308. 16 indexed citations
5.
Monzo, Pascale, Yuk Kien Chong, Andrea Ghisleni, et al.. (2021). Adaptive mechanoproperties mediated by the formin FMN1 characterize glioblastoma fitness for invasion. Developmental Cell. 56(20). 2841–2855.e8. 21 indexed citations
6.
Um, Phoebe, Beng Ti Ang, Carol Tang, et al.. (2019). Pathogenic mutations in neurofibromin identifies a leucine-rich domain regulating glioma cell invasiveness. Oncogene. 38(27). 5367–5380. 22 indexed citations
7.
Sandanaraj, Edwin, Yuk Kien Chong, See Wee Lim, et al.. (2019). A STAT3-based gene signature stratifies glioma patients for targeted therapy. Nature Communications. 10(1). 3601–3601. 75 indexed citations
8.
Chen, Bo, Edwin Sandanaraj, Boominathan Ramasamy, et al.. (2018). Non-Invasive Multimodality Imaging Directly Shows TRPM4 Inhibition Ameliorates Stroke Reperfusion Injury. Translational Stroke Research. 10(1). 91–103. 34 indexed citations
9.
Sandanaraj, Edwin, et al.. (2016). Biobanking: An Important Resource for Precision Medicine in Glioblastoma. Advances in experimental medicine and biology. 951. 47–56. 3 indexed citations
10.
Leong, Meng Fatt, et al.. (2015). Collaboration of 3D context and extracellular matrix in the development of glioma stemness in a 3D model. Biomaterials. 78. 62–73. 38 indexed citations
11.
Jiang, Xuan‐Zhao, Carol Tang, Huanhuan Gao, & Hongjuan Cui. (2014). Mechanisms of asymmetric cell divisions in Drosophila melanogaster neuroblasts. SHILAP Revista de lepidopterología. 1 indexed citations
12.
Li, Song, Cheng Wang, Edwin Sandanaraj, et al.. (2014). The SCF Slimb E3 ligase complex regulates asymmetric division to inhibit neuroblast overgrowth. EMBO Reports. 15(2). 165–174. 15 indexed citations
13.
Toh, Tan Boon, Edwin Sandanaraj, Yuk Kien Chong, et al.. (2013). A Distinct Reactive Oxygen Species Profile Confers Chemoresistance in Glioma-Propagating Cells and Associates with Patient Survival Outcome. Antioxidants and Redox Signaling. 19(18). 2261–2279. 23 indexed citations
14.
Ng, Felicia, Chou Chai, Jeanne M.M. Tan, et al.. (2012). Parkin Pathway Activation Mitigates Glioma Cell Proliferation and Predicts Patient Survival. Cancer Research. 72(10). 2543–2553. 74 indexed citations
15.
Toh, Tan Boon, Edwin Sandanaraj, Swee Seong Wong, et al.. (2012). Progenitor-like Traits Contribute to Patient Survival and Prognosis in Oligodendroglial Tumors. Clinical Cancer Research. 18(15). 4122–4135. 12 indexed citations
16.
Choudhury, Yukti, Felix Chang Tay, Dang Hoang Lam, et al.. (2012). Attenuated adenosine-to-inosine editing of microRNA-376a* promotes invasiveness of glioblastoma cells. Journal of Clinical Investigation. 122(11). 4059–4076. 164 indexed citations
17.
Sandanaraj, Edwin, Harold B. Brooks, Robert M. Campbell, et al.. (2012). Glioma-Propagating Cells as an In Vitro Screening Platform: PLK1 as a Case Study. SLAS DISCOVERY. 17(9). 1136–1150. 4 indexed citations
18.
Chai, Chou, Pei‐Jou Chua, Puay Hoon Tan, et al.. (2010). Parkin Enhances the Expression of Cyclin-dependent Kinase 6 and Negatively Regulates the Proliferation of Breast Cancer Cells*. Journal of Biological Chemistry. 285(38). 29231–29238. 93 indexed citations
19.
Tang, Carol, et al.. (2007). Chemotherapy in Adults with Gliomas. Annals of the Academy of Medicine Singapore. 36(5). 364–369. 8 indexed citations
20.
Baines, Paul, et al.. (1995). Responsiveness to stem cell factor (SCF) of peripheral blood colony-forming cells from patients with myelodysplastic syndromes (MDS). Leukemia Research. 19(8). 561–566. 7 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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