Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Specific activation and targeting of cytotoxic lymphocytes through chimeric single chains consisting of antibody-binding domains and the gamma or zeta subunits of the immunoglobulin and T-cell receptors.
19931.2k citationsZelig Eshhar, Tova Waks et al.Proceedings of the National Academy of Sciencesprofile →
Expression of immunoglobulin-T-cell receptor chimeric molecules as functional receptors with antibody-type specificity.
19891.2k citationsG. Gross, Tova Waks et al.Proceedings of the National Academy of Sciencesprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of G. Gross'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 G. Gross with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Gross more than expected).
This network shows the impact of papers produced by G. Gross. 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 G. Gross. The network helps show where G. Gross may publish in the future.
Co-authorship network of co-authors of G. Gross
This figure shows the co-authorship network connecting the top 25 collaborators of G. Gross.
A scholar is included among the top collaborators of G. Gross 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 G. Gross. G. Gross is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Eshhar, Zelig, G. Gross, & Jonathan Treisman. (1993). Modifying the specificity of T cells using chimeric Ig/TCR genes.1 indexed citations
8.
Gorochov, Guy, G. Gross, Tova Waks, & Zelig Eshhar. (1993). Anti-leucocyte function-associated antigen-1 antibodies inhibit T-cell activation following low-avidity and adhesion-independent interactions.. PubMed. 79(4). 548–55.5 indexed citations
9.
Eshhar, Zelig, Tova Waks, G. Gross, & Daniel Schindler. (1993). Specific activation and targeting of cytotoxic lymphocytes through chimeric single chains consisting of antibody-binding domains and the gamma or zeta subunits of the immunoglobulin and T-cell receptors.. Proceedings of the National Academy of Sciences. 90(2). 720–724.1248 indexed citations breakdown →
10.
Gorochov, Guy, et al.. (1992). Functional assembly of chimeric T-cell receptor chains.. PubMed. 7. 53–7.5 indexed citations
11.
Eshhar, Zelig & G. Gross. (1990). Chimeric T cell receptor which incorporates the anti-tumour specificity of a monoclonal antibody with the cytolytic activity of T cells: a model system for immunotherapeutical approach.. PubMed. 10. 27–9.19 indexed citations
12.
Gross, G., Guy Gorochov, Tova Waks, & Zelig Eshhar. (1989). Generation of effector T cells expressing chimeric T cell receptor with antibody type-specificity.. PubMed. 21(1 Pt 1). 127–30.117 indexed citations
13.
Gross, G., Tova Waks, & Zelig Eshhar. (1989). Expression of immunoglobulin-T-cell receptor chimeric molecules as functional receptors with antibody-type specificity.. Proceedings of the National Academy of Sciences. 86(24). 10024–10028.1169 indexed citations breakdown →
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.