Kenneth E. Lipson

7.7k total citations · 1 hit paper
123 papers, 6.2k citations indexed

About

Kenneth E. Lipson is a scholar working on Molecular Biology, Immunology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Kenneth E. Lipson has authored 123 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 27 papers in Immunology and 20 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Kenneth E. Lipson's work include Connective Tissue Growth Factor Research (30 papers), Angiogenesis and VEGF in Cancer (18 papers) and Systemic Sclerosis and Related Diseases (11 papers). Kenneth E. Lipson is often cited by papers focused on Connective Tissue Growth Factor Research (30 papers), Angiogenesis and VEGF in Cancer (18 papers) and Systemic Sclerosis and Related Diseases (11 papers). Kenneth E. Lipson collaborates with scholars based in United States, Germany and Switzerland. Kenneth E. Lipson's co-authors include Renato Baserga, Peter E. Huber, Amir Abdollahi, Carol Wong, Suzanne Spong, Jürgen Debus, Gerald McMahon, Hermann‐Josef Gröne, Salvatore Travali and Anthony R. Howlett and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Kenneth E. Lipson

123 papers receiving 6.0k citations

Hit Papers

CTGF is a central mediato... 2012 2026 2016 2021 2012 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Kenneth E. Lipson 3.3k 1.2k 1.1k 974 737 123 6.2k
Shelia M. Violette 2.1k 0.6× 1.2k 1.0× 1.2k 1.1× 747 0.8× 625 0.8× 71 5.2k
El–Nasir Lalani 2.7k 0.8× 1.1k 0.9× 699 0.6× 1.1k 1.1× 626 0.8× 119 5.1k
Martin Sattler 4.3k 1.3× 2.4k 1.9× 694 0.6× 1.2k 1.3× 764 1.0× 151 8.6k
Edward B. Leof 4.1k 1.2× 1.5k 1.2× 1.3k 1.1× 565 0.6× 749 1.0× 106 7.3k
Daniel Kirchhofer 2.4k 0.7× 660 0.5× 520 0.5× 1.1k 1.1× 667 0.9× 116 6.4k
Yasuhiko Nishioka 2.7k 0.8× 2.3k 1.9× 1.6k 1.5× 1.7k 1.7× 608 0.8× 239 6.4k
Masashi Adachi 4.1k 1.2× 2.8k 2.3× 552 0.5× 2.0k 2.1× 982 1.3× 83 8.1k
Masaaki Terada 3.8k 1.1× 1.6k 1.3× 541 0.5× 376 0.4× 986 1.3× 141 5.9k
Yusuke Nakamura 4.6k 1.4× 2.1k 1.7× 1.1k 1.0× 1.5k 1.5× 1.5k 2.0× 160 10.4k
Massimo Pignatelli 4.7k 1.4× 2.4k 1.9× 925 0.8× 759 0.8× 1.1k 1.5× 164 8.6k

Countries citing papers authored by Kenneth E. Lipson

Since Specialization
Citations

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

Fields of papers citing papers by Kenneth E. Lipson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kenneth E. Lipson

This figure shows the co-authorship network connecting the top 25 collaborators of Kenneth E. Lipson. A scholar is included among the top collaborators of Kenneth E. Lipson 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 Kenneth E. Lipson. Kenneth E. Lipson 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.
Zhang, Ke, Ramasatyaveni Geesala, Kenneth E. Lipson, et al.. (2024). Mechanical stress-induced connective tissue growth factor plays a critical role in intestinal fibrosis in Crohn’s-like colitis. American Journal of Physiology-Gastrointestinal and Liver Physiology. 327(2). G295–G305. 5 indexed citations
3.
Dai, Ying, Christian Schwager, Janina Hanne, et al.. (2018). Oncogene addiction and radiation oncology: effect of radiotherapy with photons and carbon ions in ALK-EML4 translocated NSCLC. Radiation Oncology. 13(1). 1–1. 41 indexed citations
4.
Jaffa, Miran A., Mulugeta Gebregziabher, Sara M. Garrett, et al.. (2018). Analysis of longitudinal semicontinuous data using marginalized two-part model. Journal of Translational Medicine. 16(1). 301–301. 3 indexed citations
6.
Makino, Katsunari, et al.. (2017). Anti-connective tissue growth factor (CTGF/CCN2) monoclonal antibody attenuates skin fibrosis in mice models of systemic sclerosis. Arthritis Research & Therapy. 19(1). 134–134. 66 indexed citations
7.
Alapati, Deepthi, Min Rong, Shaoyi Chen, et al.. (2011). Connective Tissue Growth Factor Antibody Therapy Attenuates Hyperoxia-Induced Lung Injury in Neonatal Rats. American Journal of Respiratory Cell and Molecular Biology. 45(6). 1169–1177. 54 indexed citations
8.
Inglefield, Jon R., Calin Dan Dumitru, Şefik Ş. Alkan, et al.. (2008). TLR7 Agonist 852A Inhibition of Tumor Cell Proliferation Is Dependent on Plasmacytoid Dendritic Cells and Type I IFN. Journal of Interferon & Cytokine Research. 28(4). 253–263. 30 indexed citations
9.
Timke, Carmen, Heike Zieher, Alexandra Roth, et al.. (2008). Combination of Vascular Endothelial Growth Factor Receptor/Platelet-Derived Growth Factor Receptor Inhibition Markedly Improves Radiation Tumor Therapy. Clinical Cancer Research. 14(7). 2210–2219. 116 indexed citations
10.
Ghosh, Tarun Kanti, et al.. (2007). Inhibition of in vitro tumor cell proliferation by cytokines induced by combinations of TLR or TLR and TCR agonists. International Immunopharmacology. 7(11). 1471–1482. 3 indexed citations
11.
Cheema, Asim N., Tony Hong, Nafiseh Nili, et al.. (2006). Adventitial Microvessel Formation After Coronary Stenting and the Effects of SU11218, a Tyrosine Kinase Inhibitor. Journal of the American College of Cardiology. 47(5). 1067–1075. 32 indexed citations
12.
Abdollahi, Amir, Minglun Li, Ping Gong, et al.. (2005). Inhibition of platelet-derived growth factor signaling attenuates pulmonary fibrosis. The Journal of Experimental Medicine. 201(6). 925–935. 311 indexed citations
13.
Bandt, Michel De, Véronique Ollivier, M Grossin, et al.. (2003). Blockade of Vascular Endothelial Growth Factor Receptor I (VEGF-RI), but not VEGF-RII, Suppresses Joint Destruction in the K/BxN Model of Rheumatoid Arthritis. The Journal of Immunology. 171(9). 4853–4859. 103 indexed citations
16.
Lipson, Kenneth E., Long Pang, L. Julie Huber, et al.. (1998). Inhibition of Platelet-Derived Growth Factor and Epidermal Growth Factor Receptor Signaling Events after Treatment of Cells with Specific Synthetic Inhibitors of Tyrosine Kinase Phosphorylation. Journal of Pharmacology and Experimental Therapeutics. 285(2). 844–852. 42 indexed citations
17.
Mao, Xianzhi, et al.. (1995). CCAAT‐box contributions to human thymidine kinase mRNA expression. Journal of Cellular Biochemistry. 57(4). 701–710. 5 indexed citations
18.
Lipson, Kenneth E., et al.. (1990). Sequence analysis of the human thymidine kinase gene promoter: comparison with the human PCNA promoter. DNA sequence. 1(1). 13–23. 7 indexed citations
19.
Travali, Salvatore, Kenneth E. Lipson, Dariusz Jaskulski, Evelyne Lauret, & Renato Baserga. (1988). Role of the Promoter in the Regulation of the Thymidine Kinase Gene. Molecular and Cellular Biology. 8(4). 1551–1557. 17 indexed citations
20.
Baserga, Renato, et al.. (1988). Regulation of the Expression of Cell Cycle Genes. Annals of the New York Academy of Sciences. 551(1). 283–289. 5 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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