Yoav I. Henis

9.0k total citations · 1 hit paper
159 papers, 7.3k citations indexed

About

Yoav I. Henis is a scholar working on Molecular Biology, Cell Biology and Immunology and Allergy. According to data from OpenAlex, Yoav I. Henis has authored 159 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Molecular Biology, 36 papers in Cell Biology and 23 papers in Immunology and Allergy. Recurrent topics in Yoav I. Henis's work include TGF-β signaling in diseases (37 papers), Lipid Membrane Structure and Behavior (33 papers) and Cell Adhesion Molecules Research (23 papers). Yoav I. Henis is often cited by papers focused on TGF-β signaling in diseases (37 papers), Lipid Membrane Structure and Behavior (33 papers) and Cell Adhesion Molecules Research (23 papers). Yoav I. Henis collaborates with scholars based in Israel, United States and Germany. Yoav I. Henis's co-authors include Orit Gutman, Marcelo Ehrlich, Harvey F. Lodish, Petra Knaus, Yoel Kloog, Anja Nohe, Walter Sebald, Herbert Y. Lin, Sylke Haßel and Lilach Gilboa and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Yoav I. Henis

159 papers receiving 7.2k citations

Hit Papers

Phase separation of TAZ c... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yoav I. Henis Israel 49 5.3k 1.7k 862 690 538 159 7.3k
Primal de Lanerolle United States 41 4.5k 0.8× 2.0k 1.2× 549 0.6× 777 1.1× 443 0.8× 86 6.6k
Pontus Aspenström Sweden 42 5.2k 1.0× 2.8k 1.7× 612 0.7× 750 1.1× 517 1.0× 95 7.3k
David M. Helfman United States 51 6.3k 1.2× 1.9k 1.1× 757 0.9× 489 0.7× 285 0.5× 107 8.0k
Shubha Bagrodia United States 27 5.5k 1.0× 2.3k 1.4× 1.3k 1.5× 807 1.2× 261 0.5× 39 7.4k
Monique Arpin France 43 3.3k 0.6× 1.9k 1.1× 612 0.7× 1.1k 1.6× 255 0.5× 73 6.0k
Tohru Kataoka Japan 48 6.7k 1.3× 1.7k 1.0× 651 0.8× 308 0.4× 289 0.5× 122 8.2k
Jeffrey Field United States 45 4.8k 0.9× 1.6k 0.9× 984 1.1× 243 0.4× 280 0.5× 87 6.7k
Victor A. Fried United States 33 6.3k 1.2× 2.2k 1.3× 1.4k 1.7× 498 0.7× 668 1.2× 53 8.3k
Carlo Tacchetti Italy 49 5.2k 1.0× 2.6k 1.5× 1.1k 1.3× 858 1.2× 854 1.6× 122 8.6k
Anthony I. Magee United Kingdom 52 7.4k 1.4× 2.7k 1.6× 1.2k 1.4× 432 0.6× 566 1.1× 144 10.3k

Countries citing papers authored by Yoav I. Henis

Since Specialization
Citations

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

Fields of papers citing papers by Yoav I. Henis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yoav I. Henis. 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 Yoav I. Henis. The network helps show where Yoav I. Henis may publish in the future.

Co-authorship network of co-authors of Yoav I. Henis

This figure shows the co-authorship network connecting the top 25 collaborators of Yoav I. Henis. A scholar is included among the top collaborators of Yoav I. Henis 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 Yoav I. Henis. Yoav I. Henis 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
2.
Sharma, Swati, Marcelo Ehrlich, Manqi Zhang, Gerard C. Blobe, & Yoav I. Henis. (2024). NRP1 interacts with endoglin and VEGFR2 to modulate VEGF signaling and endothelial cell sprouting. Communications Biology. 7(1). 112–112. 12 indexed citations
3.
Han, Mei, Roman Liebe, Ye Yao, et al.. (2023). The Interplay of TGF-β1 and Cholesterol Orchestrating Hepatocyte Cell Fate, EMT, and Signals for HSC Activation. Cellular and Molecular Gastroenterology and Hepatology. 17(4). 567–587. 10 indexed citations
4.
Sternberg, Hasana, et al.. (2021). Formation of self-organizing functionally distinct Rho of plants domains involves a reduced mobile population. PLANT PHYSIOLOGY. 187(4). 2485–2508. 11 indexed citations
5.
Ehrlich, Marcelo, et al.. (2018). Cholesterol depletion enhances TGF-β Smad signaling by increasing c-Jun expression through a PKR-dependent mechanism. Molecular Biology of the Cell. 29(20). 2494–2507. 12 indexed citations
6.
Varadaraj, Archana, Priyanka Singh, Anindya Chanda, et al.. (2017). TGF-β triggers rapid fibrillogenesis via a novel TβRII-dependent fibronectin-trafficking mechanism. Molecular Biology of the Cell. 28(9). 1195–1207. 27 indexed citations
7.
Hirschhorn, Tal, et al.. (2016). Differential regulation of translation and endocytosis of alternatively spliced forms of the type II bone morphogenetic protein (BMP) receptor. Molecular Biology of the Cell. 27(4). 716–730. 15 indexed citations
8.
Burgess, Antony W., Yoav I. Henis, Nancy E. Hynes, et al.. (2014). EGF receptor family: twisting targets for improved cancer therapies. Growth Factors. 32(2). 74–81. 6 indexed citations
9.
Ehrlich, Marcelo, Orit Gutman, Petra Knaus, & Yoav I. Henis. (2012). Oligomeric interactions of TGF‐β and BMP receptors. FEBS Letters. 586(14). 1885–1896. 71 indexed citations
10.
Ehrlich, Marcelo, et al.. (2011). Homomeric and heteromeric complexes among TGF-β and BMP receptors and their roles in signaling. Cellular Signalling. 23(9). 1424–1432. 66 indexed citations
11.
Sorek, Nadav, Yoav I. Henis, & Shaul Yalovsky. (2011). How prenylation and S-acylation regulate subcellular targeting and function of ROP GTPases. Plant Signaling & Behavior. 6(7). 1026–1029. 11 indexed citations
12.
Henis, Yoav I., Barak Rotblat, & Yoel Kloog. (2006). FRAP beam-size analysis to measure palmitoylation-dependent membrane association dynamics and microdomain partitioning of Ras proteins. Methods. 40(2). 183–190. 47 indexed citations
13.
Shvartsman, Dmitry, et al.. (2003). Differently anchored influenza hemagglutinin mutants display distinct interaction dynamics with mutual rafts. The Journal of Cell Biology. 163(4). 879–888. 93 indexed citations
14.
Dietrich, Alexander, Alexander Scheer, Daria Illenberger, et al.. (2003). Studies on G-protein α·βγ heterotrimer formation reveal a putative S-prenyl-binding site in the α subunit. Biochemical Journal. 376(2). 449–456. 21 indexed citations
15.
Shental-Bechor, Dalit, Tsafi Danieli, Yoav I. Henis, & Nir Ben‐Tal. (2002). Long-range effects on the binding of the influenza HA to receptors are mediated by changes in the stability of a metastable HA conformation. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1565(1). 81–90. 6 indexed citations
16.
Gilboa, Lilach, R Ben-Levy, Yosef Yarden, & Yoav I. Henis. (1995). Roles for a Cytoplasmic Tyrosine and Tyrosine Kinase Activity in the Interactions of Neu Receptors with Coated Pits. Journal of Biological Chemistry. 270(13). 7061–7067. 65 indexed citations
19.
Schreiber, Gabriel, Yoav I. Henis, & M Sokolovsky. (1987). Application of competition kinetics to investigate rat brain muscarinic receptors.. PubMed. 23(1-2). 36–43. 1 indexed citations
20.
Chet, I., et al.. (1977). Chemotaxis and movement of Physarum polycephalum and its responses to some neurotransmitters and psychomimetic compounds.. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 4(3). 177–87. 2 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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