Gil Katz

5.7k total citations
81 papers, 4.4k citations indexed

About

Gil Katz is a scholar working on Atomic and Molecular Physics, and Optics, Immunology and Electrical and Electronic Engineering. According to data from OpenAlex, Gil Katz has authored 81 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Atomic and Molecular Physics, and Optics, 24 papers in Immunology and 16 papers in Electrical and Electronic Engineering. Recurrent topics in Gil Katz's work include Immune Cell Function and Interaction (23 papers), Spectroscopy and Quantum Chemical Studies (19 papers) and Advanced Chemical Physics Studies (15 papers). Gil Katz is often cited by papers focused on Immune Cell Function and Interaction (23 papers), Spectroscopy and Quantum Chemical Studies (19 papers) and Advanced Chemical Physics Studies (15 papers). Gil Katz collaborates with scholars based in Israel, United States and France. Gil Katz's co-authors include Ofer Mandelboim, Tal I. Arnon, Ronnie Kosloff, Gal Markel, Angel Porgador, Roi Gazit, Hagit Achdout, Nissim Benvenisty, Micha Drukker and Jacob H. Hanna and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Gil Katz

80 papers receiving 4.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gil Katz Israel 30 2.3k 849 550 497 476 81 4.4k
Daniel A. Mitchell United Kingdom 41 2.5k 1.1× 2.6k 3.0× 367 0.7× 553 1.1× 365 0.8× 126 7.5k
T. Boone United States 31 1.3k 0.6× 1.3k 1.5× 749 1.4× 166 0.3× 458 1.0× 89 4.3k
Pranab K. Das Netherlands 39 1.9k 0.8× 722 0.9× 259 0.5× 566 1.1× 500 1.1× 150 5.2k
M. Matsui Japan 40 1.2k 0.5× 867 1.0× 455 0.8× 292 0.6× 375 0.8× 217 4.8k
Kensuke Inaba Japan 36 7.1k 3.1× 1.6k 1.9× 931 1.7× 537 1.1× 565 1.2× 107 9.2k
Michael Steinitz Israel 32 1.2k 0.5× 975 1.1× 462 0.8× 378 0.8× 289 0.6× 160 3.5k
Alessandra Cambi Netherlands 43 2.2k 1.0× 2.2k 2.6× 486 0.9× 470 0.9× 617 1.3× 113 5.7k
Robert Binder United States 27 3.0k 1.3× 3.2k 3.8× 525 1.0× 627 1.3× 320 0.7× 68 5.4k
Grégoire Altan‐Bonnet United States 36 2.5k 1.1× 3.3k 3.9× 1.0k 1.9× 352 0.7× 325 0.7× 76 6.8k
Takayuki Ishikawa Japan 34 813 0.4× 451 0.5× 687 1.2× 216 0.4× 740 1.6× 249 4.4k

Countries citing papers authored by Gil Katz

Since Specialization
Citations

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

Fields of papers citing papers by Gil Katz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gil Katz

This figure shows the co-authorship network connecting the top 25 collaborators of Gil Katz. A scholar is included among the top collaborators of Gil Katz 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 Gil Katz. Gil Katz 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.
Mota, Lúcio Flávio Macêdo, Diana Giannuzzi, Sara Pegolo, et al.. (2024). Combining genetic markers, on-farm information and infrared data for the in-line prediction of blood biomarkers of metabolic disorders in Holstein cattle. Journal of Animal Science and Biotechnology. 15(1). 83–83. 3 indexed citations
2.
Mota, Lúcio Flávio Macêdo, Diana Giannuzzi, Vittoria Bisutti, et al.. (2022). Real-time milk analysis integrated with stacking ensemble learning as a tool for the daily prediction of cheese-making traits in Holstein cattle. Journal of Dairy Science. 105(5). 4237–4255. 27 indexed citations
3.
Katz, Gil, Kelsey Voss, Yong Chan Kim, et al.. (2018). FOXP3 renders activated human regulatory T cells resistant to restimulation-induced cell death by suppressing SAP expression. Cellular Immunology. 327. 54–61. 13 indexed citations
4.
Katz, Gil, Pablo Piantanida, Romain Couillet, & Mérouane Debbah. (2015). On the necessity of binning for the distributed hypothesis testing problem. HAL (Le Centre pour la Communication Scientifique Directe). 2797–2801. 4 indexed citations
5.
Tai, Xuguang, Batu Erman, Amala Alag, et al.. (2013). Foxp3 Transcription Factor Is Proapoptotic and Lethal to Developing Regulatory T Cells unless Counterbalanced by Cytokine Survival Signals. Immunity. 38(6). 1116–1128. 174 indexed citations
6.
7.
Katz, Gil & Andrew L. Snow. (2013). Fluorescence-Activated Cell Sorting-Based Quantitation of T Cell Receptor Restimulation-Induced Cell Death in Activated, Primary Human T Cells. Methods in molecular biology. 979. 15–23. 9 indexed citations
8.
Rom, Naomi, Sergey V. Zybin, Adri C. T. van Duin, et al.. (2011). Mechanism change in hot dense liquid nitromethane decomposition: ReaxFF molecular dynamics simulations. Bulletin of the American Physical Society. 1 indexed citations
9.
Leitner, Gabriel, et al.. (2011). Online evaluation of milk quality according to coagulation properties for its optimal distribution for industrial applications. Journal of Dairy Science. 94(6). 2923–2932. 18 indexed citations
10.
Gruda, Raizy, Hagit Achdout, Noam Stern‐Ginossar, et al.. (2007). Intracellular Cysteine Residues in the Tail of MHC Class I Proteins Are Crucial for Extracellular Recognition by Leukocyte Ig-Like Receptor 1. The Journal of Immunology. 179(6). 3655–3661. 28 indexed citations
11.
Katz, Gil, Mark A. Ratner, & Ronnie Kosloff. (2007). Decoherence Control by Tracking a Hamiltonian Reference Molecule. Physical Review Letters. 98(20). 203006–203006. 44 indexed citations
12.
Markel, Gal, Rachel Seidman, Gil Katz, et al.. (2006). Inhibition of Human Tumor-Infiltrating Lymphocyte Effector Functions by the Homophilic Carcinoembryonic Cell Adhesion Molecule 1 Interactions. The Journal of Immunology. 177(9). 6062–6071. 49 indexed citations
13.
Katz, Gil, Tsufit Gonen‐Gross, Tal I. Arnon, et al.. (2006). Reduced KIR2DL1 Recognition of MHC Class I Molecules Presenting Phosphorylated Peptides. The Journal of Immunology. 176(11). 6762–6769. 5 indexed citations
14.
Munitz, Ariel, Ido Bachelet, Gil Katz, et al.. (2005). 2B4 (CD244) Is Expressed and Functional on Human Eosinophils. The Journal of Immunology. 174(1). 110–118. 92 indexed citations
15.
Arnon, Tal I., Hagit Achdout, Gal Markel, et al.. (2005). Inhibition of the NKp30 activating receptor by pp65 of human cytomegalovirus. Nature Immunology. 6(5). 515–523. 295 indexed citations
16.
Katz, Gil, Roi Gazit, Tal I. Arnon, et al.. (2004). MHC Class I-Independent Recognition of NK-Activating Receptor KIR2DS4. The Journal of Immunology. 173(3). 1819–1825. 81 indexed citations
17.
Gazit, Roi, Hagai Rechnitzer, Hagit Achdout, et al.. (2004). Recognition of Mycoplasma hyorhinis by CD99‐Fc molecule. European Journal of Immunology. 34(7). 2032–2040. 12 indexed citations
18.
Achdout, Hagit, Tal I. Arnon, Gal Markel, et al.. (2003). Enhanced Recognition of Human NK Receptors After Influenza Virus Infection. The Journal of Immunology. 171(2). 915–923. 63 indexed citations
19.
Bass, Alan, et al.. (2003). Psychoanalytic Supervision of the Difficult Patient. The Psychoanalytic Quarterly. 72(2). 403–438. 6 indexed citations
20.
Arnon, Tal I., et al.. (2001). Recognition of viral hemagglutinins by NKp44 but not by NKp30. European Journal of Immunology. 31(9). 2680–2689. 322 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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