Ruben Papoian

2.1k citations
35 papers · 1.4k indexed · h-index 18
Topics
Monoclonal and Polyclonal Antibodies Research (7 papers)Cell Adhesion Molecules Research (3 papers)T-cell and B-cell Immunology (3 papers)

In The Last Decade

Ruben Papoian

34 papers receiving 1.3k citations

Peers

Ruben Papoian
Comparison fields: 5 of 87
  • Immunology 538
  • Molecular Biology 447
  • Rheumatology 318
  • Reproductive Medicine 179
  • Oncology 178
Replace Takeshi Yamada with:
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Margaret M. Halloran United States
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Kiyomi Mizugishi Japan
Francesca L. Sciacca Italy
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Citations per field
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Citations per year

Countries citing papers authored by Ruben Papoian

Since Specialization
Citations

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

Fields of papers citing papers by Ruben Papoian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruben Papoian

This figure shows the co-authorship network connecting the top 25 collaborators of Ruben Papoian. A scholar is included among the top collaborators of Ruben Papoian 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 Ruben Papoian. Ruben Papoian 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
#WorkIndexed citations
1 26
2 19
3
High Throughput and High Content Screening Capabilities of the University of Cincinnati Drug Discovery Center
0
4 17
5 7
6 31
7 3
8 134
9 69
10 115
11 20
12 27
13 102
14 114
15 69
16 6
17 15
18 4
19
Immunological regulation of spontaneous antibodies to DNA and RNA. III. Early effects of neonatal thymectomy and splenectomy.
11
20
Immunological regulation of spontaneous antibodies to DNA and RNA. II. Sequential switch from IgM to IgG in NZB/NZW F1 mice.
125

About Ruben Papoian

Ruben Papoian is a scholar working on Immunology and Allergy, Immunology and Radiology, Nuclear Medicine and Imaging, having authored 35 papers that have together received 1.4k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (7 papers), Cell Adhesion Molecules Research (3 papers) and T-cell and B-cell Immunology (3 papers). The work is most often cited by research in Immunology (538 citations), Reproductive Medicine (179 citations) and Rheumatology (318 citations). Ruben Papoian has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Norman Talal, Jirayr R. Roubinian, Ursula Boschert, Rao J. Pillarisetty, Marcin P. Mycko, Krzysztof Selmaj, Cedric S. Raine, Ottaviano Serlupi‐Crescenzi, Michela Carbonatto and Marta Baiocchi. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and The Journal of Immunology.

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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