Ting Lu

724 citations
15 papers · 522 · h-index 11

Impact in

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

Papers in

    • Immune Cell Function and Interaction 11
    • IL-33, ST2, and ILC Pathways 2
    • Immunotherapy and Immune Responses 2
    • CAR-T cell therapy research 4
    • Cancer Immunotherapy and Biomarkers 2

Ting Lu

15 papers receiving 519 citations

Peers

Ting Lu
Comparison fields: 5 of 75
  • Immunology 291
  • Oncology 336
  • Modeling and Simulation 18
  • Genetics 87
  • Cancer Research 39
Replace Valentina Casella with:
Valentina Casella Spain
Ranjan Upadhyay United States
Jean‐Christophe Beltra United States
Erika J. Crosby United States
Elien M. Doorduijn Netherlands
Mara Valentini Italy
Capucine L. Grandjean France
Aleksei Titov Russia
D. Byrd United States
Jessica Michie Australia
Ting Lu relative to Valentina Casella Spain Valentina Casella's profile →
Citations per field
00.5×2.6×
Valentina Casella · 1×
Citations per year

Countries citing papers authored by Ting Lu

Since Specialization
Citations

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

Fields of papers citing papers by Ting Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2021162
2 202295
3 201446
4 202239
5 202234
6 202228
7 202327
8 202124
9 202013
10 202212
11 201811
12 201910
13 20219
14 20247
15 20245

About Ting Lu

Ting Lu is a scholar working on Immunology, Oncology, Hematology, Genetics and Biomedical Engineering, having authored 15 papers that have together received 522 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (11 papers), CAR-T cell therapy research (4 papers), IL-33, ST2, and ILC Pathways (2 papers), Immunotherapy and Immune Responses (2 papers), Autoimmune and Inflammatory Disorders Research (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), 3D Printing in Biomedical Research (1 paper) and Glioma Diagnosis and Treatment (1 paper). The work is most often cited by research in Immunology (291 citations), Oncology (336 citations), Modeling and Simulation (18 citations), Genetics (87 citations) and Cancer Research (39 citations). Ting Lu has collaborated with scholars based in United States and China. Frequent co-authors include Jianhua Yu, Michael A. Caligiuri, Jianying Zhang, Anthony G. Mansour, Lei Tian, Kun‐Yu Teng, Bo Xu, Shoubao Ma, Tasha Barr and Rui Ma. Their work appears in journals such as Cancer Immunology Research, Virus Research, The Journal of Immunology, Gastroenterology and Nature Communications.

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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