Alan T. Tang

1.8k total citations
20 papers, 685 citations indexed

About

Alan T. Tang is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Alan T. Tang has authored 20 papers receiving a total of 685 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Neurology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Alan T. Tang's work include Vascular Malformations Diagnosis and Treatment (4 papers), Neonatal Respiratory Health Research (3 papers) and Intracranial Aneurysms: Treatment and Complications (3 papers). Alan T. Tang is often cited by papers focused on Vascular Malformations Diagnosis and Treatment (4 papers), Neonatal Respiratory Health Research (3 papers) and Intracranial Aneurysms: Treatment and Complications (3 papers). Alan T. Tang collaborates with scholars based in United States, Germany and Australia. Alan T. Tang's co-authors include Mark L. Kahn, William B. Campbell, Kasem Nithipatikom, Jisheng Yang, Xiangjian Zheng, Robert Shenkar, Issam A. Awad, Lorne S. Parnes, Sharika Bamezai and Alexander C. Wright and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Alan T. Tang

18 papers receiving 674 citations

Peers

Alan T. Tang

NEURO

CCM

SURGE

CMN

Priya Umapathi United States

Don H. Bark United States

Silvia Bonanno Italy

Zhe Huang Japan

Teruaki Masuda Japan

Bilal Malik United States

Manfred Lange Germany

Matteo Garibaldi Italy

Marcos Barbosa Portugal

Abderahim Gaceb Sweden

Priya Umapathi United States

Alan T. Tang

203 ×0.9

NEURO

566 ×3.4

191 ×1.6

CCM

73 ×1.1

SURGE

84 ×1.3

CMN

Citations per year, relative to Alan T. Tang Alan T. Tang (= 1×) peers Priya Umapathi

Countries citing papers authored by Alan T. Tang

Since Specialization

Citations

This map shows the geographic impact of Alan T. 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 Alan T. Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alan T. Tang more than expected).

Fields of papers citing papers by Alan T. Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alan T. Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Alan T. Tang. A scholar is included among the top collaborators of Alan T. 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 Alan T. Tang. Alan T. 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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20 of 20 papers shown

Chen, Xiaowen, Joanna Tober, Martin H. Dominguez, et al.. (2025). Lineage tracing studies suggest that the placenta is not a de novo source of hematopoietic stem cells. PLoS Biology. 23(1). e3003003–e3003003. 1 indexed citations

Zhao, Gan, Prashant Chandrasekaran, Xinyuan Li, et al.. (2024). Dynamic behavior and lineage plasticity of the pulmonary venous endothelium. Nature Cardiovascular Research. 3(12). 1584–1600. 3 indexed citations

Vallon, Mario, Jie Ding, Alan T. Tang, et al.. (2024). GPR124 regulates murine brain embryonic angiogenesis and BBB formation by an intracellular domain-independent mechanism. Development. 151(11). 5 indexed citations

Gao, Siqi, Alan T. Tang, David W. Buchholz, et al.. (2023). Endothelial SARS-CoV-2 infection is not the underlying cause of COVID-19-associated vascular pathology in mice. Frontiers in Cardiovascular Medicine. 10. 4 indexed citations

Sung, Derek C., Mei Chen, Martin H. Dominguez, et al.. (2022). Sinusoidal and lymphatic vessel growth is controlled by reciprocal VEGF-C–CDH5 inhibition. Nature Cardiovascular Research. 1(11). 1006–1021. 7 indexed citations

Johnson, N. M., Alan T. Tang, Yuhua Tian, et al.. (2022). Limitations to Understanding Intestinal Stem Cell Activity via Cre-Lox–Based Lineage Tracing. Cellular and Molecular Gastroenterology and Hepatology. 14(6). 1334–1337.e1.

Chen, Xiaowen, Alan T. Tang, Joanna Tober, et al.. (2022). Mouse placenta fetal macrophages arise from endothelial cells outside the placenta. Developmental Cell. 57(23). 2652–2660.e3. 13 indexed citations

Keller, T.C. Stevenson, Lillian Yuxian Lim, Swapnil V. Shewale, et al.. (2021). Genetic blockade of lymphangiogenesis does not impair cardiac function after myocardial infarction. Journal of Clinical Investigation. 131(20). 39 indexed citations

Zafar, Atif, Syed A. Quadri, Mudassir Farooqui, et al.. (2019). Familial Cerebral Cavernous Malformations. Stroke. 50(5). 1294–1301. 76 indexed citations

10.

McIntyre, William F., et al.. (2018). CARDIAC RESYNCHRONIZATION IS PRO-ARRHYTHMIC IN THE ABSENCE OF REVERSE VENTRICULAR REMODELLING: A SYSTEMATIC REVIEW AND META-ANALYSIS. Canadian Journal of Cardiology. 34(10). S134–S135.

11.

Ma, Peisong, Shuchi Gupta, Valerie Tutwiler, et al.. (2018). RGS10 shapes the hemostatic response to injury through its differential effects on intracellular signaling by platelet agonists. Blood Advances. 2(16). 2145–2155. 15 indexed citations

12.

Zhao, Jichao, Brian J. Hansen, Yufeng Wang, et al.. (2017). Three‐dimensional Integrated Functional, Structural, and Computational Mapping to Define the Structural “Fingerprints” of Heart‐Specific Atrial Fibrillation Drivers in Human Heart Ex Vivo. Journal of the American Heart Association. 6(8). 103 indexed citations

13.

Girard, Romuald, Hussein A. Zeineddine, Courtney P. Orsbon, et al.. (2016). Micro-computed tomography in murine models of cerebral cavernous malformations as a paradigm for brain disease. Journal of Neuroscience Methods. 271. 14–24. 16 indexed citations

14.

Zhou, Zinan, Alan T. Tang, Sharika Bamezai, et al.. (2016). Cerebral cavernous malformations arise from endothelial gain of MEKK3–KLF2/4 signalling. Nature. 532(7597). 122–126. 211 indexed citations

15.

Zheng, Xiangjian, Florence Riant, Françoise Bergametti, et al.. (2014). Cerebral Cavernous Malformations Arise Independent of the Heart of Glass Receptor. Stroke. 45(5). 1505–1509. 17 indexed citations

16.

Tang, Alan T., William B. Campbell, & Kasem Nithipatikom. (2012). ROCK1 feedback regulation of the upstream small GTPase RhoA. Cellular Signalling. 24(7). 1375–1380. 31 indexed citations

17.

Nithipatikom, Kasem, et al.. (2011). Cannabinoid Receptor Type 1 (CB1) Activation Inhibits Small GTPase RhoA Activity and Regulates Motility of Prostate Carcinoma Cells. Endocrinology. 153(1). 29–41. 34 indexed citations

18.

Nithipatikom, Kasem, Alan T. Tang, Vijaya L. Manthati, et al.. (2010). Inhibition of carcinoma cell motility by epoxyeicosatrienoic acid (EET) antagonists. Cancer Science. 101(12). 2629–2636. 37 indexed citations

19.

Pirih, Flávia Q., et al.. (2004). Nuclear Orphan Receptor Nurr1 Directly Transactivates the Osteocalcin Gene in Osteoblasts. Journal of Biological Chemistry. 279(51). 53167–53174. 46 indexed citations

20.

Tang, Alan T. & Lorne S. Parnes. (1994). X-Linked Progressive Mixed Hearing Loss: Computed Tomography Findings. Annals of Otology Rhinology & Laryngology. 103(8). 655–657. 27 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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