Lanzhen Yan

1.0k citations
15 papers · 552 · 1 hit paper · h-index 11

Impact in

Papers in

    • CRISPR and Genetic Engineering 4
    • Ubiquitin and proteasome pathways 2
    • Pluripotent Stem Cells Research 2
    • Single-cell and spatial transcriptomics 2
    • RNA modifications and cancer 2
    • Cancer-related Molecular Pathways 2
    • Pancreatic and Hepatic Oncology Research 2

Lanzhen Yan

14 papers receiving 547 citations

Lanzhen Yan's Hit Papers

NKG2D-CAR T cells eliminate senescent cells in aged mice and nonhuman primates 2023 · 133 citations
1330+1+2Years since publication4080120

Peers

Lanzhen Yan
Comparison fields: 5 of 67
  • Aging 15
  • Oncology 131
  • Immunology 88
  • Cancer Research 60
  • Molecular Biology 279
Replace Ilse G.L. Pauli with:
Ilse G.L. Pauli Belgium
Lijiang Fei China
Ivan Bedzhov Germany
Andrea L. Marat Canada
Vernadeth B. Alarcón United States
Cristina Claverı́a Spain
Néstor Saiz United States
Walter Carbone Switzerland
Márta P. Imreh Sweden
Nadine Schrode United States
Lanzhen Yan relative to Ilse G.L. Pauli Belgium Ilse G.L. Pauli's profile →
Citations per field
00.5×10×15×21×
Ilse G.L. Pauli · 1×
Citations per year

Countries citing papers authored by Lanzhen Yan

Since Specialization
Citations

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

Fields of papers citing papers by Lanzhen Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1
NKG2D-CAR T cells eliminate senescent cells in aged mice and nonhuman primates
Hit paper breakdown →
2023133
2 202179
3 201662
4 201853
5 201743
6 201737
7 200535
8 201929
9 201823
10 202321
11 201720
12 20199
13 20165
14 20213
15 20060

About Lanzhen Yan

Lanzhen Yan is a scholar working on Molecular Biology, Oncology, Immunology, Surgery and Genetics, having authored 15 papers that have together received 552 indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (4 papers), Ubiquitin and proteasome pathways (2 papers), Pluripotent Stem Cells Research (2 papers), Single-cell and spatial transcriptomics (2 papers), Cancer-related Molecular Pathways (2 papers), Pancreatic and Hepatic Oncology Research (2 papers), RNA modifications and cancer (2 papers) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Aging (15 citations), Oncology (131 citations), Immunology (88 citations), Cancer Research (60 citations) and Molecular Biology (279 citations). Lanzhen Yan has collaborated with scholars based in China and United States. Frequent co-authors include Xudong Zhao, Bin Sun, Dong Yang, Nan Liu, Xianning Zhang, Shirong Li, Yibin Deng, Xiuyun Liu, Xiaoyue Cui and Wenwen Wei. Their work appears in journals such as Cell Research, Journal of Hematology & Oncology, Oncogene, Oncotarget and Disease Models & Mechanisms.

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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