Weining Tang

2.0k total citations
19 papers, 1.6k citations indexed

About

Weining Tang is a scholar working on Molecular Biology, Plant Science and Cancer Research. According to data from OpenAlex, Weining Tang has authored 19 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 6 papers in Plant Science and 5 papers in Cancer Research. Recurrent topics in Weining Tang's work include Plant Molecular Biology Research (5 papers), Molecular Biology Techniques and Applications (3 papers) and Plant nutrient uptake and metabolism (3 papers). Weining Tang is often cited by papers focused on Plant Molecular Biology Research (5 papers), Molecular Biology Techniques and Applications (3 papers) and Plant nutrient uptake and metabolism (3 papers). Weining Tang collaborates with scholars based in United States, China and Canada. Weining Tang's co-authors include Sharyn E. Perry, Mark Bouzyk, Brian Leyland‐Jones, Donna E. Fernandez, Karl W. Nichols, Dhiraj Thakare, Kristine Hill, Susheng Gan, Thomas Jack and Yuehui He and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Immunology and JNCI Journal of the National Cancer Institute.

In The Last Decade

Weining Tang

19 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weining Tang United States 18 954 661 247 219 217 19 1.6k
Liping Xu China 22 659 0.7× 248 0.4× 213 0.9× 132 0.6× 270 1.2× 55 1.4k
Silvère Baron France 20 495 0.5× 140 0.2× 228 0.9× 208 0.9× 212 1.0× 47 1.3k
Jing Jia China 21 490 0.5× 406 0.6× 55 0.2× 188 0.9× 115 0.5× 49 1.1k
Jingfei Cheng United States 27 1.1k 1.2× 815 1.2× 57 0.2× 104 0.5× 100 0.5× 40 1.9k
Hyun Seok Kim South Korea 20 890 0.9× 138 0.2× 160 0.6× 204 0.9× 245 1.1× 45 1.4k
Maxim Ivanov Denmark 17 823 0.9× 309 0.5× 98 0.4× 120 0.5× 164 0.8× 27 1.1k
Ning Qing Liu Netherlands 17 743 0.8× 146 0.2× 104 0.4× 71 0.3× 124 0.6× 39 1.1k
Ben Van Houten United States 17 1.0k 1.1× 117 0.2× 109 0.4× 255 1.2× 201 0.9× 20 1.5k
David M. Truong United States 17 952 1.0× 121 0.2× 389 1.6× 96 0.4× 46 0.2× 25 1.4k
Yoshitaka Tomigahara Japan 14 627 0.7× 141 0.2× 69 0.3× 187 0.9× 79 0.4× 47 1.0k

Countries citing papers authored by Weining Tang

Since Specialization
Citations

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

Fields of papers citing papers by Weining Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weining Tang

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

All Works

19 of 19 papers shown
1.
Gao, Ran, et al.. (2018). LncRNA LOXL1-AS1 Promotes the Proliferation and Metastasis of Medulloblastoma by Activating the PI3K/AKT Pathway. Analytical Cellular Pathology. 2018. 1–11. 63 indexed citations
2.
Wang, Jian, et al.. (2016). Plumbagin Mediates Cardioprotection Against Myocardial Ischemia/Reperfusion Injury Through Nrf-2 Signaling. Medical Science Monitor. 22. 1250–1257. 30 indexed citations
3.
Dey, Nandini, Benjamin G. Barwick, Carlos S. Moreno, et al.. (2013). Wnt signaling in triple negative breast cancer is associated with metastasis. BMC Cancer. 13(1). 537–537. 215 indexed citations
4.
Regan, Meredith M., Brian Leyland‐Jones, Mark Bouzyk, et al.. (2012). CYP2D6 Genotype and Tamoxifen Response in Postmenopausal Women with Endocrine-Responsive Breast Cancer: The Breast International Group 1-98 Trial. JNCI Journal of the National Cancer Institute. 104(6). 441–451. 229 indexed citations
5.
Taylor, Kira C., Chanley M. Small, Celia E. Dominguez, et al.. (2011). Alcohol, Smoking, and Caffeine in Relation to Fecundability, with Effect Modification by NAT2. Annals of Epidemiology. 21(11). 864–872. 19 indexed citations
6.
Abramovitz, Mark, Benjamin G. Barwick, Scooter Willis, et al.. (2011). Molecular characterisation of formalin-fixed paraffin-embedded (FFPE) breast tumour specimens using a custom 512-gene breast cancer bead array-based platform. British Journal of Cancer. 105(10). 1574–1581. 17 indexed citations
7.
Shehata, Bahig M., et al.. (2011). Identification of Candidate Genes for Histiocytoid Cardiomyopathy (HC) Using Whole Genome Expression Analysis: Analyzing Material from the HC Registry. Pediatric and Developmental Pathology. 14(5). 370–377. 8 indexed citations
8.
Barwick, Benjamin G., Mark Abramovitz, Maja Kodani, et al.. (2010). Prostate cancer genes associated with TMPRSS2–ERG gene fusion and prognostic of biochemical recurrence in multiple cohorts. British Journal of Cancer. 102(3). 570–576. 50 indexed citations
9.
Boštík, Pavel, Weining Tang, François Villinger, et al.. (2009). Decreased NK Cell Frequency and Function Is Associated with Increased Risk of KIR3DL Allele Polymorphism in Simian Immunodeficiency Virus-Infected Rhesus Macaques with High Viral Loads. The Journal of Immunology. 182(6). 3638–3649. 44 indexed citations
10.
Tang, Weining, et al.. (2009). DNA Extraction from Formalin-Fixed, Paraffin-Embedded Tissue. Cold Spring Harbor Protocols. 2009(2). pdb.prot5138–pdb.prot5138. 30 indexed citations
11.
Teras, Lauren R., Michael Goodman, Alpa V. Patel, et al.. (2009). No Association between Polymorphisms in LEP, LEPR, ADIPOQ, ADIPOR1, or ADIPOR2 and Postmenopausal Breast Cancer Risk. Cancer Epidemiology Biomarkers & Prevention. 18(9). 2553–2557. 46 indexed citations
12.
Su, Shaoyong, Jinying Zhao, J. Douglas Bremner, et al.. (2009). Serotonin Transporter Gene, Depressive Symptoms, and Interleukin-6. Circulation Cardiovascular Genetics. 2(6). 614–620. 50 indexed citations
13.
Feigelson, Heather Spencer, Lauren R. Teras, W. Ryan Diver, et al.. (2008). Genetic variation in candidate obesity genes ADRB2, ADRB3, GHRL, HSD11B1, IRS1, IRS2, and SHC1 and risk for breast cancer in the Cancer Prevention Study II. Breast Cancer Research. 10(4). R57–R57. 44 indexed citations
14.
Thakare, Dhiraj, Weining Tang, Kristine Hill, & Sharyn E. Perry. (2008). The MADS-Domain Transcriptional Regulator AGAMOUS-LIKE15 Promotes Somatic Embryo Development in Arabidopsis and Soybean. PLANT PHYSIOLOGY. 146(4). 1663–1672. 129 indexed citations
15.
Tang, Weining, et al.. (2003). Binding Site Selection for the Plant MADS Domain Protein AGL15. Journal of Biological Chemistry. 278(30). 28154–28159. 105 indexed citations
16.
Tang, Weining, et al.. (2003). Expression and Maintenance of Embryogenic Potential Is Enhanced through Constitutive Expression ofAGAMOUS-Like 15 . PLANT PHYSIOLOGY. 133(2). 653–663. 185 indexed citations
17.
18.
He, Yuehui, et al.. (2001). Networking Senescence-Regulating Pathways by Using Arabidopsis Enhancer Trap Lines. PLANT PHYSIOLOGY. 126(2). 707–716. 175 indexed citations
19.

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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