David E. Carter

6.7k total citations
33 papers, 1.3k citations indexed

About

David E. Carter is a scholar working on Molecular Biology, Cell Biology and Immunology and Allergy. According to data from OpenAlex, David E. Carter has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 6 papers in Cell Biology and 6 papers in Immunology and Allergy. Recurrent topics in David E. Carter's work include Connective Tissue Growth Factor Research (8 papers), Cell Adhesion Molecules Research (6 papers) and Connective tissue disorders research (3 papers). David E. Carter is often cited by papers focused on Connective Tissue Growth Factor Research (8 papers), Cell Adhesion Molecules Research (6 papers) and Connective tissue disorders research (3 papers). David E. Carter collaborates with scholars based in Canada, United States and United Kingdom. David E. Carter's co-authors include Andrew Leask, Feng Guo, Shiwen Xu, Shangxi Liu, Daphne Pala, Laura Kennedy, David Abraham, Carol M. Black, Mark Eastwood and Yunliang Chen and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and FEBS Letters.

In The Last Decade

David E. Carter

32 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David E. Carter Canada 20 638 193 179 161 156 33 1.3k
Sándor Szántó Hungary 29 506 0.8× 123 0.6× 187 1.0× 183 1.1× 107 0.7× 81 2.3k
Wenxia Wang China 18 325 0.5× 127 0.7× 297 1.7× 86 0.5× 235 1.5× 52 1.1k
Ryusuke Yoshimi Japan 23 328 0.5× 93 0.5× 91 0.5× 88 0.5× 156 1.0× 84 1.4k
Alon Ben‐Arie Israel 20 296 0.5× 166 0.9× 106 0.6× 71 0.4× 72 0.5× 74 1.5k
Howard A. Chansky United States 23 916 1.4× 428 2.2× 94 0.5× 83 0.5× 345 2.2× 46 1.8k
Ralph Lachman United States 26 840 1.3× 378 2.0× 175 1.0× 230 1.4× 196 1.3× 68 2.8k
Helen D. Brasch New Zealand 22 591 0.9× 504 2.6× 139 0.8× 50 0.3× 190 1.2× 66 1.3k
Masahito Horiguchi Japan 17 898 1.4× 328 1.7× 52 0.3× 224 1.4× 299 1.9× 21 2.0k
Inaam A. Nakchbandi Germany 27 775 1.2× 215 1.1× 58 0.3× 241 1.5× 182 1.2× 48 2.0k
Günther A. Rezniczek Germany 24 585 0.9× 537 2.8× 125 0.7× 608 3.8× 126 0.8× 73 2.0k

Countries citing papers authored by David E. Carter

Since Specialization
Citations

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

Fields of papers citing papers by David E. Carter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Carter. 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 David E. Carter. The network helps show where David E. Carter may publish in the future.

Co-authorship network of co-authors of David E. Carter

This figure shows the co-authorship network connecting the top 25 collaborators of David E. Carter. A scholar is included among the top collaborators of David E. Carter 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 David E. Carter. David E. Carter 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.
Xu, Shiwen, John Nguyen, David E. Carter, et al.. (2023). Tripterygium wilfordii derivative celastrol, a YAP inhibitor, has antifibrotic effects in systemic sclerosis. Annals of the Rheumatic Diseases. 82(9). 1191–1204. 15 indexed citations
2.
Gill, Sean E., Claúdia C. dos Santos, David B. O’Gorman, et al.. (2020). Transcriptional profiling of leukocytes in critically ill COVID19 patients: implications for interferon response and coagulation. Intensive Care Medicine Experimental. 8(1). 75–75. 34 indexed citations
3.
Carter, David E., et al.. (2019). Hyperactive TORC 1 sensitizes yeast cells to endoplasmic reticulum stress by compromising cell wall integrity. FEBS Letters. 593(15). 1957–1973. 13 indexed citations
4.
Fraser, Douglas D., Eric K. Patterson, Claudio M. Martin, et al.. (2015). Human severe sepsis cytokine mixture increases β2-integrin-dependent polymorphonuclear leukocyte adhesion to cerebral microvascular endothelial cells in vitro. Critical Care. 19(1). 149–149. 19 indexed citations
5.
Vincent, Krista M., et al.. (2015). CCN2 Expression by Tumor Stroma Is Required for Melanoma Metastasis. Journal of Investigative Dermatology. 135(11). 2805–2813. 32 indexed citations
6.
Johansen, Christopher T., Joseph B. Dubé, David E. Carter, et al.. (2014). LipidSeq: a next-generation clinical resequencing panel for monogenic dyslipidemias. Journal of Lipid Research. 55(4). 765–772. 103 indexed citations
7.
Guo, Feng, et al.. (2013). TAK1 Is Required for Dermal Wound Healing and Homeostasis. Journal of Investigative Dermatology. 133(6). 1646–1654. 25 indexed citations
8.
Cox, Aaron R., et al.. (2013). Cellular mechanisms underlying failed beta cell regeneration in offspring of protein-restricted pregnant mice. Experimental Biology and Medicine. 238(10). 1147–1159. 15 indexed citations
9.
Roy, Ashbeel, Aline Lara, Rita Gomes Wanderley Pires, et al.. (2012). An Analysis of the Myocardial Transcriptome in a Mouse Model of Cardiac Dysfunction with Decreased Cholinergic Neurotransmission. PLoS ONE. 7(6). e39997–e39997. 9 indexed citations
10.
11.
Yazdan-Ashoori, Payam, Patricia C. Liaw, Lisa J. Toltl, et al.. (2011). Elevated plasma matrix metalloproteinases and their tissue inhibitors in patients with severe sepsis. Journal of Critical Care. 26(6). 556–565. 58 indexed citations
12.
Lagares, David, Óscar Busnadiego, Rosa A. García‐Fernández, et al.. (2011). Inhibition of focal adhesion kinase prevents experimental lung fibrosis and myofibroblast formation. Arthritis & Rheumatism. 64(5). 1653–1664. 136 indexed citations
13.
Guo, Feng, David E. Carter, & Andrew Leask. (2011). Mechanical Tension Increases CCN2/CTGF Expression and Proliferation in Gingival Fibroblasts via a TGFβ-Dependent Mechanism. PLoS ONE. 6(5). e19756–e19756. 72 indexed citations
14.
Chen, Yunliang, Andrew Leask, David Abraham, et al.. (2008). Heparan sulfate–dependent ERK activation contributes to the overexpression of fibrotic proteins and enhanced contraction by scleroderma fibroblasts. Arthritis & Rheumatism. 58(2). 577–585. 39 indexed citations
15.
16.
Chen, Shaoqiong, Sarah McLean, David E. Carter, & Andrew Leask. (2007). The gene expression profile induced by Wnt 3a in NIH 3T3 fibroblasts. Journal of Cell Communication and Signaling. 1(3-4). 175–183. 49 indexed citations
17.
Xu, Shiwen, Laura Kennedy, Daphne Pala, et al.. (2006). CCN2 Is Necessary for Adhesive Responses to Transforming Growth Factor-β1 in Embryonic Fibroblasts. Journal of Biological Chemistry. 281(16). 10715–10726. 136 indexed citations
18.
Kennedy, Laura, Shangxi Liu, Shiwen Xu, et al.. (2006). CCN2 is necessary for the function of mouse embryonic fibroblasts. Experimental Cell Research. 313(5). 952–964. 78 indexed citations
19.
Carter, David E., et al.. (2005). Glucose Dependence of the Regulated Secretory Pathway in αTC1-6 Cells. Endocrinology. 146(10). 4514–4523. 47 indexed citations
20.
Carter, David E., John F. Robinson, Emma M. Allister, Murray W. Huff, & Robert A. Hegele. (2005). Quality assessment of microarray experiments. Clinical Biochemistry. 38(7). 639–642. 8 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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