Irit Sagi

11.9k citations
141 papers · 8.1k · 1 hit paper · h-index 50

Impact in

Papers in

Irit Sagi

139 papers receiving 7.9k citations

Irit Sagi's Hit Papers

The extracellular matrix protein agrin promotes heart regeneration in mice 2017 · 495 citations
4950+3+6Years since publication100200300400

Peers

Irit Sagi
Comparison fields: 5 of 164
  • Biomaterials 1.5k
  • Cancer Research 1.4k
  • Immunology and Allergy 450
  • Oncology 1.6k
  • Paleontology 417
Replace Peter V. Hauschka with:
Peter V. Hauschka United States
Walter Keller Austria
Takeshi Kasama Japan
Peter M. Frederik Netherlands
Boris Turk Slovenia
Max M. Burger Switzerland
Melvin J. Glimcher United States
Qin Yan China
Hiroshi Miyamoto United States
Yan Liu China
Irit Sagi relative to Peter V. Hauschka United States Peter V. Hauschka's profile →
Citations per field
00.5×5×10.1×
Peter V. Hauschka · 1×
Citations per year

Countries citing papers authored by Irit Sagi

Since Specialization
Citations

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

Fields of papers citing papers by Irit Sagi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Irit Sagi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Irit Sagi Line = papers co-authored together Irit Sagi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 141 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The extracellular matrix protein agrin promotes heart regeneration in mice
Hit paper breakdown →
2017495
2 2008385
3 2005301
4 2016285
5 1992263
6 2019256
7 2009225
8 2008205
9 2006204
10 2002193
11 2011174
12 2020162
13 2017155
14 2017139
15 2011136
16 2009131
17 2010111
18 2003110
19 2016108
20 2016102

About Irit Sagi

Irit Sagi is a scholar working on Molecular Biology, Cancer Research, Oncology, Immunology and Allergy and Immunology, having authored 141 papers that have together received 8.1k indexed citations. Recurring topics across this work include Protease and Inhibitor Mechanisms (44 papers), Peptidase Inhibition and Analysis (31 papers), Cell Adhesion Molecules Research (14 papers), Signaling Pathways in Disease (13 papers), RNA and protein synthesis mechanisms (11 papers), Blood Coagulation and Thrombosis Mechanisms (7 papers), Enzyme Structure and Function (7 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). The work is most often cited by research in Biomaterials (1.5k citations), Cancer Research (1.4k citations), Immunology and Allergy (450 citations), Oncology (1.6k citations) and Paleontology (417 citations). Irit Sagi has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Lia Addadi, Steve Weiner, Inna Solomonov, Yael Udi, Yael Politi, Vishnu Mohan, Alakesh Das, Moran Grossman, Yael Levi‐Kalisman and Sefi Raz. Their work appears in journals such as Journal of Biological Chemistry, Journal of the American Chemical Society, Proceedings of the National Academy of Sciences, Biochemistry and PLoS ONE.

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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