Gabriel Salzman

658 total citations
9 papers, 448 citations indexed

About

Gabriel Salzman is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Nephrology. According to data from OpenAlex, Gabriel Salzman has authored 9 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 1 paper in Nephrology. Recurrent topics in Gabriel Salzman's work include Receptor Mechanisms and Signaling (5 papers), Neuropeptides and Animal Physiology (3 papers) and Glycosylation and Glycoproteins Research (1 paper). Gabriel Salzman is often cited by papers focused on Receptor Mechanisms and Signaling (5 papers), Neuropeptides and Animal Physiology (3 papers) and Glycosylation and Glycoproteins Research (1 paper). Gabriel Salzman collaborates with scholars based in United States, Netherlands and Denmark. Gabriel Salzman's co-authors include Shohei Koide, Ankit Gupta, Demet Araç, Fern Sha, Yue Lü, Akiko Koide, Nan‐Sheng Li, Richard Sando, Thomas C. Südhof and Gregory G. Tall and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Blood.

In The Last Decade

Gabriel Salzman

8 papers receiving 446 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gabriel Salzman United States	7	355	155	102	58	47	9	448
Arthur Marivin United States	17	469 1.3×	102 0.7×	39 0.4×	40 0.7×	58 1.2×	22	574
Akvile Haeckel Germany	9	212 0.6×	108 0.7×	62 0.6×	23 0.4×	26 0.6×	13	423
M.R. Nance United States	8	351 1.0×	96 0.6×	24 0.2×	53 0.9×	43 0.9×	9	490
Kathrin Zuberbühler United States	5	289 0.8×	64 0.4×	136 1.3×	19 0.3×	116 2.5×	5	468
Alexander Vizurraga United States	5	214 0.6×	105 0.7×	56 0.5×	38 0.7×	18 0.4×	6	268
Fu‐Yue Zeng United States	16	755 2.1×	333 2.1×	107 1.0×	21 0.4×	86 1.8×	31	891
H. Uri Saragovi Canada	11	300 0.8×	181 1.2×	127 1.2×	27 0.5×	69 1.5×	13	487
Nikoleta G. Tsvetanova United States	11	654 1.8×	248 1.6×	54 0.5×	18 0.3×	34 0.7×	17	754
Maria H. Knoppers United States	7	365 1.0×	57 0.4×	84 0.8×	28 0.5×	19 0.4×	9	477
Deep Chatterjee Germany	14	312 0.9×	74 0.5×	25 0.2×	12 0.2×	47 1.0×	28	463

Countries citing papers authored by Gabriel Salzman

Since Specialization

Citations

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

Fields of papers citing papers by Gabriel Salzman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabriel Salzman

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Salzman. A scholar is included among the top collaborators of Gabriel Salzman 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 Gabriel Salzman. Gabriel Salzman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Salzman, Gabriel & Ann Mullally. (2025). Novel strategies targeting mutant calreticulin in essential thrombocythemia and myelofibrosis. Blood. 147(12). 1267–1277.

Salzman, Gabriel, Shu Zhang, Celia Fernandez, Demet Araç, & Shohei Koide. (2020). Specific and direct modulation of the interaction between adhesion GPCR GPR56/ADGRG1 and tissue transglutaminase 2 using synthetic ligands. Scientific Reports. 10(1). 16912–16912. 14 indexed citations

Skubák, Pavol, Demet Araç, Matthew W. Bowler, et al.. (2018). A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model. IUCrJ. 5(2). 166–171. 33 indexed citations

Winkler, Jana Barbro, Katherine Leon, Hannah M. Stoveken, et al.. (2018). A Comprehensive Mutagenesis Screen of the Adhesion GPCR Latrophilin-1/ADGRL1. iScience. 3. 264–278. 40 indexed citations

Sha, Fern, Gabriel Salzman, Ankit Gupta, & Shohei Koide. (2017). Monobodies and other synthetic binding proteins for expanding protein science. Protein Science. 26(5). 910–924. 120 indexed citations

Leon, Katherine, Yue Lü, Richard Sando, et al.. (2017). Structural and Functional Studies of Latrophilin‐Family Adhesion G‐Protein Coupled Receptors. The FASEB Journal. 31(S1). 1 indexed citations

Salzman, Gabriel, Shu Zhang, Ankit Gupta, et al.. (2017). Stachel-independent modulation of GPR56/ADGRG1 signaling by synthetic ligands directed to its extracellular region. Proceedings of the National Academy of Sciences. 114(38). 10095–10100. 54 indexed citations

Salzman, Gabriel, Sarah D. Ackerman, Chen Ding, et al.. (2016). Structural Basis for Regulation of GPR56/ADGRG1 by Its Alternatively Spliced Extracellular Domains. Neuron. 91(6). 1292–1304. 90 indexed citations

Lü, Yue, Richard Sando, Gabriel Salzman, et al.. (2015). Structural Basis of Latrophilin-FLRT-UNC5 Interaction in Cell Adhesion. Structure. 23(9). 1678–1691. 96 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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