George Tang

1.2k citations
39 papers · 837 indexed · h-index 14

Impact in

  • Hematology top 5%
    • Multiple Myeloma Research and Treatments
  • Hepatology top 10%
    • Hepatitis C virus research

Papers in

    • Multiple Myeloma Research and Treatments 19
    • Myeloproliferative Neoplasms: Diagnosis and Treatment 5
    • Chronic Lymphocytic Leukemia Research 3

George Tang

39 papers receiving 803 citations

Peers

George Tang
Comparison fields: 5 of 88
  • Hematology 189
  • Hepatology 86
  • Endocrinology, Diabetes and Metabolism 141
  • Oncology 201
  • Pharmacology 62
Replace Stephan Bek with:
Stephan Bek Germany
Shipra Agrawal United States
S. Vishnupriya India
Munetaka Ozeki Japan
Saeed Daneshmandi Iran
Ulrich Kohnert Germany
Ming Zhou China
Manfred G. Ismair Switzerland
George Tang relative to Stephan Bek Germany Stephan Bek's profile →
Citations per field
00.5×5.7×
Stephan Bek · 1×
Citations per year

Countries citing papers authored by George Tang

Since Specialization
Citations

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

Fields of papers citing papers by George Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20241
2 202413
3 202318
4 20212
5 201913
6 201838
7 201718
8 20176
9 20171
10 201711
11 201735
12 20172
13 201687
14 20161
15 201510
16 20146
17 20147
18
The CYP3A4*1B variant is related to the onset of puberty, a known risk factor for the development of breast cancer.
200383
19 199715
20 199710

About George Tang

George Tang is a scholar working on Hematology, Genetics, Radiology, Nuclear Medicine and Imaging, Oncology and Molecular Biology, having authored 39 papers that have together received 837 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (19 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers), Protein Degradation and Inhibitors (5 papers), Glycosylation and Glycoproteins Research (4 papers), Chronic Lymphocytic Leukemia Research (3 papers), Peptidase Inhibition and Analysis (3 papers) and Research on Leishmaniasis Studies (2 papers). The work is most often cited by research in Hematology (189 citations), Hepatology (86 citations), Endocrinology, Diabetes and Metabolism (141 citations), Oncology (201 citations) and Pharmacology (62 citations). George Tang has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Vay Liang W. Go, Hongxiang Hui, Eric Sanchez, James R. Berenson, Mingjie Li, Cathy S. Wang, Haiming Chen, Camilia Soof, Haiming Chen and Jake P. Mann. Their work appears in journals such as Blood, Clinical Cancer Research, British Journal of Haematology, Nature Communications and Leukemia Research.

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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