Lan Le

15 papers receiving 247 citations

Peers

Lan Le
Comparison fields: 5 of 59
  • Cancer Research 51
  • Critical Care and Intensive Care Medicine 12
  • Oncology 68
  • Immunology 40
  • Pulmonary and Respiratory Medicine 50
Replace Attilio Antonio Montano Bianchi with:
Attilio Antonio Montano Bianchi Italy
Georgina L. Eden Australia
Yunle Wan China
Jiangyue Qin China
Han Han China
Shuting Wu China
Nicola Trim United Kingdom
Yiqin Xia China
Michael Williamson Ireland
Nicole L. Jansing United States
Lan Le relative to Attilio Antonio Montano Bianchi Italy Attilio Antonio Montano Bianchi's profile →
Citations per field
00.5×4.2×
Attilio Antonio Montano Bianchi · 1×
Citations per year

Countries citing papers authored by Lan Le

Since Specialization
Citations

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

Fields of papers citing papers by Lan Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1
G2M checkpoint pathway alone is associated with drug response and survival among cell proliferation-related pathways in pancreatic cancer.
202146
2 202038
3 202133
4 202123
5 202223
6 202217
7 200514
8 202013
9 202312
10 202311
11 20186
12 20246
13 20245
14 20212
15 20192
16 20250
17 20210
18 20210

About Lan Le

Lan Le is a scholar working on Pulmonary and Respiratory Medicine, Oncology, Cancer Research, Molecular Biology and Artificial Intelligence, having authored 18 papers that have together received 251 indexed citations. Recurring topics across this work include Ferroptosis and cancer prognosis (5 papers), Pancreatic and Hepatic Oncology Research (3 papers), Cancer Genomics and Diagnostics (3 papers), Cancer Immunotherapy and Biomarkers (3 papers), Cancer-related molecular mechanisms research (2 papers), Imbalanced Data Classification Techniques (1 paper), Angiogenesis and VEGF in Cancer (1 paper) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Cancer Research (51 citations), Critical Care and Intensive Care Medicine (12 citations), Oncology (68 citations), Immunology (40 citations) and Pulmonary and Respiratory Medicine (50 citations). Lan Le has collaborated with scholars based in United States, Japan and Thailand. Frequent co-authors include Kazuaki Takabe, Masanori Oshi, Yoshihisa Tokumaru, Li Yan, Itaru Endo, Ryusei Matsuyama, Manabu Futamura, Ankit Patel, Eriko Katsuta and Nobuhisa Matsuhashi. Their work appears in journals such as Journal of Clinical Oncology, Frontiers in Public Health, Chemical Science, Journal of Thoracic Oncology and International Journal of Molecular Sciences.

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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