Jacqueline Wang

555 citations
20 papers · 279 · h-index 9

Impact in

    • Cancer Immunotherapy and Biomarkers
    • CAR-T cell therapy research
    • Lung Cancer Research Studies
    • Multiple Myeloma Research and Treatments

Papers in

Jacqueline Wang

16 papers receiving 277 citations

Peers

Jacqueline Wang
Comparison fields: 5 of 66
  • Oncology 125
  • Hematology 42
  • Genetics 33
  • Cancer Research 37
  • Immunology 36
Replace K Govind Babu with:
K Govind Babu India
Michelle Purdom United States
Kyung‐Hun Lee South Korea
Sreekanth Reddy United States
Damé Idossa United States
Sara Nunnery United States
Kelsey Klute United States
Thomas Gwise United States
Rabih Said United States
Yong Mun United States
Jacqueline Wang relative to K Govind Babu India K Govind Babu's profile →
Citations per field
00.5×7.5×
K Govind Babu · 1×
Citations per year

Countries citing papers authored by Jacqueline Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jacqueline Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2020113
2 202139
3 201532
4 201716
5 201916
6 201716
7 201514
8 200810
9 20248
10 20246
11 20203
12 20112
13 20221
14 20231
15 20241
16 20231
17 20240
18 20150
19 20210
20 20250

About Jacqueline Wang

Jacqueline Wang is a scholar working on Oncology, Pathology and Forensic Medicine, Molecular Biology, Pulmonary and Respiratory Medicine and Genetics, having authored 20 papers that have together received 279 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (6 papers), Chronic Lymphocytic Leukemia Research (3 papers), Cancer Immunotherapy and Biomarkers (3 papers), Protein Degradation and Inhibitors (2 papers), CAR-T cell therapy research (2 papers), Cutaneous lymphoproliferative disorders research (2 papers), Cancer Genomics and Diagnostics (2 papers) and Lung Cancer Treatments and Mutations (2 papers). The work is most often cited by research in Oncology (125 citations), Hematology (42 citations), Genetics (33 citations), Cancer Research (37 citations) and Immunology (36 citations). Jacqueline Wang has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Jill S. Barnholtz‐Sloan, Carol Kruchko, Yucai Wang, Joshua B. Rubin, Kristin Waite, Fang Yang, Justin D. Lathia, Michael E. Berens, Gino Cioffi and Quinn T. Ostrom. Their work appears in journals such as Blood, iScience, JNCI Journal of the National Cancer Institute, Scientific Reports and Molecular Diagnosis & Therapy.

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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