Bin Lian

3.7k citations
156 papers · 1.9k · h-index 23

Impact in

  • Oncology top 2%
    • Cutaneous Melanoma Detection and Management
    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers
  • Immunology top 10%
    • Immunotherapy and Immune Responses

Papers in

    • Cutaneous Melanoma Detection and Management 43
    • Cancer Immunotherapy and Biomarkers 35
    • CAR-T cell therapy research 28
    • Melanoma and MAPK Pathways 29

Bin Lian

139 papers receiving 1.9k citations

Peers

Bin Lian
Comparison fields: 5 of 105
  • Oncology 987
  • Immunology 292
  • Cancer Research 170
  • Ophthalmology 74
  • Molecular Biology 591
Replace Jabed Iqbal with:
Jabed Iqbal Singapore
Bruce G. Ward Australia
Marc F. Hansen United States
Joseph J. Sacco United Kingdom
Pamela Kearns United Kingdom
Katy K. Tsai United States
H.J. Hoekstra Netherlands
Anastasia Constantinidou Cyprus
Emma V. King United Kingdom
David Arguello United States
Bin Lian relative to Jabed Iqbal Singapore Jabed Iqbal's profile →
Citations per field
00.5×6.2×
Jabed Iqbal · 1×
Citations per year

Countries citing papers authored by Bin Lian

Since Specialization
Citations

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

Fields of papers citing papers by Bin Lian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 156 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020193
2 2013122
3 201699
4 201384
5 201774
6 201649
7 201547
8 202243
9 201338
10 201838
11 202136
12 201836
13 202236
14 201736
15 202235
16 201932
17 201832
18 202030
19 202230
20 202227

About Bin Lian

Bin Lian is a scholar working on Oncology, Molecular Biology, Pulmonary and Respiratory Medicine, Immunology and Cancer Research, having authored 156 papers that have together received 1.9k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (43 papers), Cancer Immunotherapy and Biomarkers (35 papers), Melanoma and MAPK Pathways (29 papers), CAR-T cell therapy research (28 papers), Immunotherapy and Immune Responses (14 papers), Renal cell carcinoma treatment (12 papers), Virus-based gene therapy research (11 papers) and Bladder and Urothelial Cancer Treatments (10 papers). The work is most often cited by research in Oncology (987 citations), Immunology (292 citations), Cancer Research (170 citations), Ophthalmology (74 citations) and Molecular Biology (591 citations). Bin Lian has collaborated with scholars based in China, Ethiopia and United States. Frequent co-authors include Lu Si, Xinan Sheng, Chuanliang Cui, Jun Guo, Zhihong Chi, Bixia Tang, Yan Kong, Lili Mao, Xieqiao Yan and Li Zhou. Their work appears in journals such as Journal of Clinical Oncology, Annals of Oncology, European Journal of Cancer, Frontiers in Oncology and Clinical Cancer 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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