Mohammad Tabrizi

1.8k citations
26 papers · 1.3k · h-index 14

Impact in

Papers in

Mohammad Tabrizi

26 papers receiving 1.2k citations

Peers

Mohammad Tabrizi
Comparison fields: 5 of 92
  • Radiology, Nuclear Medicine and Imaging 460
  • Immunology 389
  • Oncology 354
  • Molecular Biology 554
  • Cancer Research 111
Replace Makoto Kamachi with:
Makoto Kamachi Japan
Mark R. Albertini United States
Christopher McKenzie United Kingdom
Yubin Kang United States
Maury Rosenstein United States
Christian Rudlowski Germany
Douglas Orr United States
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B Van Camp Belgium
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Mohammad Tabrizi relative to Makoto Kamachi Japan Makoto Kamachi's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mohammad Tabrizi

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Tabrizi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohammad Tabrizi, 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 Mohammad Tabrizi Line = papers co-authored together Mohammad Tabrizi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006367
2 2009220
3 2004198
4 2010113
5 2011105
6
Macrophages from motheaten and viable motheaten mutant mice show increased proliferative responses to GM-CSF: detection of potential HCP substrates in GM-CSF signal transduction.
199774
7 200923
8 201521
9 200920
10 201018
11 200716
12 200915
13 201215
14 201013
15 200812
16 201311
17 201910
18 20195
19 20204
20 20183

About Mohammad Tabrizi

Mohammad Tabrizi is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology, Immunology, Oncology and Pulmonary and Respiratory Medicine, having authored 26 papers that have together received 1.3k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (16 papers), Protein purification and stability (7 papers), Biosimilars and Bioanalytical Methods (6 papers), Glycosylation and Glycoproteins Research (5 papers), CAR-T cell therapy research (4 papers), Immune Cell Function and Interaction (3 papers), Immunotherapy and Immune Responses (3 papers) and HER2/EGFR in Cancer Research (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (460 citations), Immunology (389 citations), Oncology (354 citations), Molecular Biology (554 citations) and Cancer Research (111 citations). Mohammad Tabrizi has collaborated with scholars based in United States, United Kingdom and Iran. Frequent co-authors include Lorin Roskos, Gadi Gazit Bornstein, Saling Huang, Gregory Bell, Donald A. Mahler, David C. Blakey, Scott L. Klakamp, Wentian Yang, Karim Berrada and T Yi. Their work appears in journals such as The AAPS Journal, Drug Discovery Today, Cancer Research, Molecular Cancer Therapeutics and Blood.

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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