Thomas T. Poulsen

938 total citations
33 papers, 627 citations indexed

About

Thomas T. Poulsen is a scholar working on Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Thomas T. Poulsen has authored 33 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 10 papers in Molecular Biology and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Thomas T. Poulsen's work include Monoclonal and Polyclonal Antibodies Research (7 papers), HER2/EGFR in Cancer Research (6 papers) and Lung Cancer Treatments and Mutations (6 papers). Thomas T. Poulsen is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (7 papers), HER2/EGFR in Cancer Research (6 papers) and Lung Cancer Treatments and Mutations (6 papers). Thomas T. Poulsen collaborates with scholars based in Denmark, United States and Spain. Thomas T. Poulsen's co-authors include Rasmus Lema, Hans Skovgaard Poulsen, Michael Kragh, Ivan D. Horak, Johan Lantto, Charlotte Bay Hasager, Camilla L. Christensen, Helle J. Jacobsen, Mikkel W. Pedersen and Anna Dahlman and has published in prestigious journals such as Journal of Clinical Oncology, Renewable and Sustainable Energy Reviews and Cancer Research.

In The Last Decade

Thomas T. Poulsen

32 papers receiving 604 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Thomas T. Poulsen 246 196 155 84 79 33 627
Lingmei Wang 228 0.9× 352 1.8× 37 0.2× 74 0.9× 85 1.1× 42 944
Tao Ouyang 568 2.3× 328 1.7× 181 1.2× 69 0.8× 174 2.2× 117 1.3k
Lvhua Wang 118 0.5× 125 0.6× 207 1.3× 22 0.3× 230 2.9× 35 706
Caixia Cheng 188 0.8× 198 1.0× 208 1.3× 14 0.2× 133 1.7× 38 692
Domenico Gattuso 268 1.1× 195 1.0× 46 0.3× 18 0.2× 94 1.2× 65 767
Yehui Shi 203 0.8× 183 0.9× 24 0.2× 62 0.7× 76 1.0× 77 581
Ting Xiao 352 1.4× 693 3.5× 42 0.3× 235 2.8× 224 2.8× 95 1.4k
Patrick Carroll 342 1.4× 427 2.2× 35 0.2× 15 0.2× 51 0.6× 21 969
Yongjie Wang 209 0.8× 591 3.0× 45 0.3× 153 1.8× 193 2.4× 99 1.2k
Qing Zou 236 1.0× 555 2.8× 117 0.8× 57 0.7× 188 2.4× 102 1.6k

Countries citing papers authored by Thomas T. Poulsen

Since Specialization
Citations

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

Fields of papers citing papers by Thomas T. Poulsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas T. Poulsen

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas T. Poulsen. A scholar is included among the top collaborators of Thomas T. Poulsen 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 Thomas T. Poulsen. Thomas T. Poulsen 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
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Sánchez-Martín, Francisco Javier, Oriol Arpí, Laura Visa, et al.. (2019). HER-Family Ligands Promote Acquired Resistance to Trastuzumab in Gastric Cancer. Molecular Cancer Therapeutics. 18(11). 2135–2145. 42 indexed citations
3.
Kristensen, Lotte K., Camilla Fröhlich, Camilla L. Christensen, et al.. (2019). CD4+ and CD8a+ PET imaging predicts response to novel PD-1 checkpoint inhibitor: studies of Sym021 in syngeneic mouse cancer models. Theranostics. 9(26). 8221–8238. 66 indexed citations
4.
Camidge, D. Ross, Filip Jankú, Daniel V.T. Catenacci, et al.. (2019). A phase Ia/IIa trial of Sym015, a MET antibody mixture, in patients with advanced solid tumours. Annals of Oncology. 30. v610–v611. 3 indexed citations
5.
Calvert, Valerie, Shruti Rao, Simina M. Boca, et al.. (2018). Acquired Resistance to a MET Antibody In Vivo Can Be Overcome by the MET Antibody Mixture Sym015. Molecular Cancer Therapeutics. 17(6). 1259–1270. 9 indexed citations
6.
Poulsen, Thomas T., Michael M. Grandal, Klaus Koefoed, et al.. (2017). Sym015: A Highly Efficacious Antibody Mixture against MET -Amplified Tumors. Clinical Cancer Research. 23(19). 5923–5935. 42 indexed citations
7.
Grandal, Michael M., Thomas T. Poulsen, Klaus Koefoed, et al.. (2017). Simultaneous Targeting of Two Distinct Epitopes on MET Effectively Inhibits MET- and HGF-Driven Tumor Growth by Multiple Mechanisms. Molecular Cancer Therapeutics. 16(12). 2780–2791. 23 indexed citations
8.
Bardelli, Alberto, Thomas T. Poulsen, Rodrigo Dienstmann, et al.. (2017). Genotyping circulating tumor DNA identifies metastatic colorectal cancer (mCRC) patients highly sensitive to Sym004. Annals of Oncology. 28. v34–v34. 1 indexed citations
9.
Tabernero, Josep, Fortunato Ciardiello, Clara Montagut, et al.. (2017). Efficacy and safety of Sym004 in refractory metastatic colorectal cancer with acquired resistance to anti-EGFR therapy: Results of a randomized phase II study (RP2S). Annals of Oncology. 28. v160–v160. 2 indexed citations
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Poulsen, Thomas T. & Charlotte Bay Hasager. (2016). How Expensive Is Expensive Enough? Opportunities for Cost Reductions in Offshore Wind Energy Logistics. Energies. 9(6). 437–437. 22 indexed citations
12.
Jacobsen, Helle J., Thomas T. Poulsen, Anna Dahlman, et al.. (2015). Pan-HER, an Antibody Mixture Simultaneously Targeting EGFR, HER2, and HER3, Effectively Overcomes Tumor Heterogeneity and Plasticity. Clinical Cancer Research. 21(18). 4110–4122. 71 indexed citations
13.
Pedersen, Mikkel W., Helle J. Jacobsen, Klaus Koefoed, et al.. (2015). Targeting Three Distinct HER2 Domains with a Recombinant Antibody Mixture Overcomes Trastuzumab Resistance. Molecular Cancer Therapeutics. 14(3). 669–680. 42 indexed citations
14.
Nielsen, Carsten H., Mette Munk Jensen, Lotte K. Kristensen, et al.. (2015). In vivoimaging of therapy response to a novel Pan-HER antibody mixture using FDG and FLT positron emission tomography. Oncotarget. 6(35). 37486–37499. 12 indexed citations
15.
Poulsen, Thomas T.. (2015). Changing Strategies in Global Wind Energy Shipping, Logistics, and Supply Chain Management. 83–106. 5 indexed citations
16.
Christensen, Camilla L., et al.. (2012). Insertion of a nuclear factor kappa B DNA nuclear-targeting sequence potentiates suicide gene therapy efficacy in lung cancer cell lines. Cancer Gene Therapy. 19(10). 675–683. 24 indexed citations
17.
18.
Poulsen, Thomas T., Nina Marie Pedersen, Helene Bæk Juel, & Hans Skovgaard Poulsen. (2008). A chimeric fusion of the hASH1 and EZH2 promoters mediates high and specific reporter and suicide gene expression and cytotoxicity in small cell lung cancer cells. Cancer Gene Therapy. 15(9). 563–575. 17 indexed citations
19.
Poulsen, Thomas T., et al.. (2005). Specific sensitivity of small cell lung cancer cell lines to the snake venom toxin taipoxin. Lung Cancer. 50(3). 329–337. 10 indexed citations
20.
Poulsen, Thomas T., Nina Marie Pedersen, & Hans Skovgaard Poulsen. (2005). Replacement and Suicide Gene Therapy for Targeted Treatment of Lung Cancer. Clinical Lung Cancer. 6(4). 227–236. 19 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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