Phong Quang

2.0k citations
31 papers · 1.2k · h-index 13

Impact in

Papers in

    • PI3K/AKT/mTOR signaling in cancer 6
    • Ubiquitin and proteasome pathways 2
    • Multiple Myeloma Research and Treatments 13
    • Chronic Myeloid Leukemia Treatments 3

Phong Quang

31 papers receiving 1.2k citations

Peers

Phong Quang
Comparison fields: 5 of 76
  • Hematology 323
  • Cancer Research 256
  • Genetics 173
  • Oncology 272
  • Molecular Biology 731
Replace Yawara Kawano with:
Yawara Kawano Japan
Yoko Ueno Japan
Marcus M. Schittenhelm Germany
Clara Guerzoni Italy
Siobhan Glavey United States
Daniel Ratschiller Switzerland
Leila R. Martins Portugal
Monica Minischetti Italy
Sanjay Koul United States
Susanne Hipp Germany
Phong Quang relative to Yawara Kawano Japan Yawara Kawano's profile →
Citations per field
00.5×1.5×1.8×
Yawara Kawano · 1×
Citations per year

Countries citing papers authored by Phong Quang

Since Specialization
Citations

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

Fields of papers citing papers by Phong Quang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016290
2 2012239
3 2012120
4 201198
5 201091
6 200981
7 201167
8 201065
9 201134
10 201125
11 201120
12 201412
13 201312
14 20117
15 20115
16 20115
17 20114
18 20123
19 20093
20 20092

About Phong Quang

Phong Quang is a scholar working on Molecular Biology, Hematology, Genetics, Oncology and Pathology and Forensic Medicine, having authored 31 papers that have together received 1.2k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (13 papers), Chronic Lymphocytic Leukemia Research (11 papers), PI3K/AKT/mTOR signaling in cancer (6 papers), Chemokine receptors and signaling (5 papers), Lymphoma Diagnosis and Treatment (4 papers), Hematological disorders and diagnostics (3 papers), Chronic Myeloid Leukemia Treatments (3 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Hematology (323 citations), Cancer Research (256 citations), Genetics (173 citations), Oncology (272 citations) and Molecular Biology (731 citations). Phong Quang has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Irene M. Ghobrial, Patricia Maiso, Feda Azab, Abdel Kareem Azab, Hai T. Ngo, Antonio Sacco, Aldo M. Roccaro, Charles P. Lin, Costas Pitsillides and Judith Runnels. Their work appears in journals such as Blood, Clinical Cancer Research, Cell Reports, PLoS ONE and Therapeutic Advances in Hematology.

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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