David Weiss

11.9k total citations
205 papers, 9.2k citations indexed

About

David Weiss is a scholar working on Molecular Biology, Plant Science and Immunology. According to data from OpenAlex, David Weiss has authored 205 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Molecular Biology, 72 papers in Plant Science and 53 papers in Immunology. Recurrent topics in David Weiss's work include Plant Molecular Biology Research (35 papers), Plant Gene Expression Analysis (29 papers) and Plant Reproductive Biology (25 papers). David Weiss is often cited by papers focused on Plant Molecular Biology Research (35 papers), Plant Gene Expression Analysis (29 papers) and Plant Reproductive Biology (25 papers). David Weiss collaborates with scholars based in Israel, United States and Netherlands. David Weiss's co-authors include Naomi Ori, Susan Lurie, Mohammed A. Attia, Alexander Vainstein, Neil E. Olszewski, Eran Pichersky, Abraham H. Halevy, Gili Ben‐Nissan, Amihud Borochov and I. Nir and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

David Weiss

196 papers receiving 8.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Weiss Israel 54 5.1k 5.1k 1.1k 791 740 205 9.2k
Lars Rask Sweden 67 7.2k 1.4× 3.0k 0.6× 3.9k 3.5× 170 0.2× 619 0.8× 237 13.3k
Olof Emanuelsson Sweden 23 8.3k 1.6× 3.5k 0.7× 374 0.3× 263 0.3× 247 0.3× 33 10.8k
David A. Jones United Kingdom 60 5.2k 1.0× 6.3k 1.2× 671 0.6× 543 0.7× 58 0.1× 205 12.5k
Lorian Schaeffer United States 5 7.1k 1.4× 2.8k 0.6× 858 0.8× 311 0.4× 154 0.2× 6 11.0k
Pang‐Chui Shaw Hong Kong 45 3.3k 0.7× 1.3k 0.3× 1.2k 1.1× 368 0.5× 129 0.2× 252 6.0k
Yasukazu Nakamura Japan 55 6.4k 1.3× 4.1k 0.8× 326 0.3× 524 0.7× 77 0.1× 206 11.0k
Takashi Okamoto Japan 63 11.4k 2.2× 1.8k 0.4× 1.8k 1.6× 253 0.3× 96 0.1× 264 16.9k
Philippe Pinton France 40 1.8k 0.4× 3.3k 0.6× 420 0.4× 364 0.5× 112 0.2× 98 5.8k
Michael G. Murray United States 26 5.5k 1.1× 8.4k 1.7× 207 0.2× 842 1.1× 138 0.2× 46 12.5k
Takuya Ito Japan 40 4.2k 0.8× 4.4k 0.9× 190 0.2× 469 0.6× 177 0.2× 196 8.5k

Countries citing papers authored by David Weiss

Since Specialization
Citations

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

Fields of papers citing papers by David Weiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Weiss

This figure shows the co-authorship network connecting the top 25 collaborators of David Weiss. A scholar is included among the top collaborators of David Weiss 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 Weiss. David Weiss 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.
Liu, Yue, Chunli Zhang, Chenyang Guo, et al.. (2024). SlSPA3 regulates the nuclear abundance of SlUVR8 in tomato. The Plant Journal. 120(6). 2656–2667.
2.
Shohat, Hagai, Himabindu Vasuki Kilambi, Natanella Illouz‐Eliaz, et al.. (2021). Inhibition of gibberellin accumulation by water deficiency promotes fast and long‐term ‘drought avoidance’ responses in tomato. New Phytologist. 232(5). 1985–1998. 56 indexed citations
3.
Panda, Sayantan, Adam Jóźwiak, Prashant D. Sonawane, et al.. (2021). Steroidal alkaloids defence metabolism and plant growth are modulated by the joint action of gibberellin and jasmonate signalling. New Phytologist. 233(3). 1220–1237. 51 indexed citations
4.
Illouz‐Eliaz, Natanella, et al.. (2020). Mutations in the tomato gibberellin receptors suppress xylem proliferation and reduce water loss under water-deficit conditions. Journal of Experimental Botany. 71(12). 3603–3612. 51 indexed citations
5.
Shohat, Hagai, Natanella Illouz‐Eliaz, Yuri Kanno, Mitsunori Seo, & David Weiss. (2020). The Tomato DELLA Protein PROCERA Promotes Abscisic Acid Responses in Guard Cells by Upregulating an Abscisic Acid Transporter. PLANT PHYSIOLOGY. 184(1). 518–528. 34 indexed citations
6.
Nir, I., Hagai Shohat, Irina Panizel, et al.. (2017). The Tomato DELLA Protein PROCERA Acts in Guard Cells to Promote Stomatal Closure. The Plant Cell. 29(12). 3186–3197. 86 indexed citations
7.
Steiner, Evyatar, Osnat Yanai, Idan Efroni, et al.. (2012). Class I TCPs modulate cytokinin-induced branching and meristematic activity in tomato. Plant Signaling & Behavior. 7(7). 807–810. 26 indexed citations
8.
Varbanova, Marina, Shinjiro Yamaguchi, Yang Yue, et al.. (2007). Methylation of Gibberellins by Arabidopsis GAMT1 and GAMT2. The Plant Cell. 19(1). 32–45. 211 indexed citations
9.
Alvarez, John Paul, et al.. (2004). Cross Talk between Gibberellin and Cytokinin: The Arabidopsis GA Response Inhibitor SPINDLY Plays a Positive Role in Cytokinin Signaling. The Plant Cell. 17(1). 92–102. 275 indexed citations
10.
Vedder‐Weiss, Dana, Édouard Jurkevitch, Saul Burdman, David Weiss, & Yaacov Okon. (1999). Root Growth, Respiration and β-Glucosidase Activity in Maize (Zea mays) and Common Bean (Phaseolus vulgaris) Inoculated with Azospirillum brasilense. Symbiosis. 26(4). 363–377. 11 indexed citations
11.
Borochov, Amihud, et al.. (1995). Methyl jasmonate induces pigmentation and flavonoid gene expression in petunia corollas: a possible role in wound response [anthocyanins, chalcone synthase, dihydroflavonol 4-reductase]. 1 indexed citations
12.
13.
14.
Weiss, David. (1980). Tumor antigenicity and approaches to tumor immunotherapy. An outline.. PubMed. 89. 1–83. 5 indexed citations
15.
Wainberg, Mark A., et al.. (1975). Reactivity of serum from rous‐sarcoma‐bearing chickens with autochthonous and with allogeneic tumor cells: Preferential autochthonous recognition. International Journal of Cancer. 15(6). 985–994. 5 indexed citations
16.
Zuckerman, A. & David Weiss. (1973). Dynamic aspects of host-parasite relationships. Academic Press eBooks. 39 indexed citations
17.
Weiss, David. (1969). Immunologic parameters of host-tumor relationships: spontaneous mammary neoplasia of the inbred mouse as a model.. PubMed. 29(12). 2368–73. 11 indexed citations
18.
Lavrin, David H., Phyllis B. Blair, & David Weiss. (1966). Immunology of Spontaneous Mammary Carcinomas in Mice. Cancer Research. 26(5). 293–304. 66 indexed citations
19.
Lavrin, David H., M Dezfulian, & David Weiss. (1965). The antigen responsible for acquired resistance to spontaneous mammary carcinomas in mice. Abstr.. The Mouseion at the JAXlibrary (Jackson Laboratory). 1 indexed citations
20.
Weiss, David & René Dubos. (1955). ANTITUBERCULOUS IMMUNITY INDUCED IN MICE BY VACCINATION WITH KILLED TUBERCLE BACILLI OR WITH A SOLUBLE BACILLARY EXTRACT. The Journal of Experimental Medicine. 101(3). 313–330. 26 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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