Lan Huang

12.3k citations
294 papers · 8.8k · h-index 52

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Immunology top 2%
    • Immune cells in cancer
    • Immune Cell Function and Interaction

Papers in

Lan Huang

279 papers receiving 8.7k citations

Peers

Lan Huang
Comparison fields: 5 of 175
  • Cancer Research 1.1k
  • Immunology 1.2k
  • Oncology 1.3k
  • Nephrology 325
  • Molecular Biology 2.8k
Replace Norbert Frey with:
Norbert Frey Germany
Ali Mobasheri United Kingdom
Yun Liu China
Xiaojie Wang China
Yan Chen China
Fan Zhang China
Jennifer E. Van Eyk United States
Bin Liu China
Kai Zhang China
Michael Roth Switzerland
Lan Huang relative to Norbert Frey Germany Norbert Frey's profile →
Citations per field
00.5×1.5×2.0×
Norbert Frey · 1×
Citations per year

Countries citing papers authored by Lan Huang

Since Specialization
Citations

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

Fields of papers citing papers by Lan Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 294 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006366
2 2013232
3 2013216
4 2021210
5 2009188
6 2019156
7 2007141
8 2021140
9 1997139
10 2019135
11 2008131
12 2006129
13 2004127
14 2010118
15 2017116
16 2016100
17 201197
18 201293
19 201992
20 200987

About Lan Huang

Lan Huang is a scholar working on Molecular Biology, Oncology, Cancer Research, Immunology and Pulmonary and Respiratory Medicine, having authored 294 papers that have together received 8.8k indexed citations. Recurring topics across this work include Angiogenesis and VEGF in Cancer (23 papers), High Altitude and Hypoxia (17 papers), Immune Cell Function and Interaction (14 papers), Cancer-related molecular mechanisms research (13 papers), MicroRNA in disease regulation (11 papers), Cancer Immunotherapy and Biomarkers (9 papers), Cancer, Hypoxia, and Metabolism (9 papers) and Immune cells in cancer (9 papers). The work is most often cited by research in Cancer Research (1.1k citations), Immunology (1.2k citations), Oncology (1.3k citations), Nephrology (325 citations) and Molecular Biology (2.8k citations). Lan Huang has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Martin Kulldorff, Mingbao Song, Yaoming Song, Linda W. Pickle, Luiz H. Duczmal, Yi Zhang, Gang Zhao, Huanliang Liu, Kevin Konty and Xiaohui Zhao. Their work appears in journals such as Cell Death and Disease, PLoS ONE, Biomedicine & Pharmacotherapy, Cytotherapy and Scientific Reports.

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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