David Weng

1.6k citations
43 papers · 1.2k · h-index 19

Impact in

  • Immunology top 5%
    • Immunotherapy and Immune Responses
    • T-cell and B-cell Immunology
    • Immune Cell Function and Interaction
  • Oncology top 10%
    • CAR-T cell therapy research

Papers in

    • Cell death mechanisms and regulation 4
    • Cancer therapeutics and mechanisms 4
    • CAR-T cell therapy research 6
    • Cancer Treatment and Pharmacology 5

David Weng

43 papers receiving 1.2k citations

Peers

David Weng
Comparison fields: 5 of 93
  • Immunology 419
  • Oncology 300
  • Cancer Research 120
  • Molecular Biology 527
  • Sensory Systems 32
Replace Amin Al-Shami with:
Amin Al-Shami United States
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Citations per field
00.5×5.3×
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Citations per year

Countries citing papers authored by David Weng

Since Specialization
Citations

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

Fields of papers citing papers by David Weng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997170
2 2015106
3 200098
4 200184
5 199978
6 199866
7 200564
8 199961
9 201555
10
Inhibition of the conversion of 3T3 fibroblast clones to adipocytes by dehydroepiandrosterone and related anticarcinogenic steroids.
198652
11 200934
12 201232
13 200029
14 200028
15 201324
16 201122
17 200622
18 201321
19 199821
20 199316

About David Weng

David Weng is a scholar working on Molecular Biology, Oncology, Immunology, Cancer Research and Pulmonary and Respiratory Medicine, having authored 43 papers that have together received 1.2k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (7 papers), CAR-T cell therapy research (6 papers), T-cell and B-cell Immunology (5 papers), Cancer Treatment and Pharmacology (5 papers), Cell death mechanisms and regulation (4 papers), Immune Cell Function and Interaction (4 papers), Cancer therapeutics and mechanisms (4 papers) and interferon and immune responses (3 papers). The work is most often cited by research in Immunology (419 citations), Oncology (300 citations), Cancer Research (120 citations), Molecular Biology (527 citations) and Sensory Systems (32 citations). David Weng has collaborated with scholars based in United States, Malaysia and Switzerland. Frequent co-authors include Nassim Usman, Peter A. Cohen, Brian J. Czerniecki, Gary K. Koski, Ravi K. Amaravadi, Martin A. Graham, Alex A. Adjei, Russell J. Schilder, Gregory E. Plautz and Liaomin Peng. Their work appears in journals such as Journal of Clinical Oncology, Cancer Research, Molecular Cancer Therapeutics, Blood 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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