Dan Lan

923 citations
42 papers · 640 indexed · h-index 13

Impact in

Papers in

    • Muscle Physiology and Disorders 7
    • RNA Research and Splicing 3
    • Blood disorders and treatments 7

Dan Lan

39 papers receiving 630 citations

Peers

Dan Lan
Comparison fields: 5 of 85
  • Geriatrics and Gerontology 72
  • Critical Care and Intensive Care Medicine 57
  • Physiology 31
  • Immunology 138
  • Emergency Medicine 60
Replace Wei Guan with:
Wei Guan China
Min-Ji Charng Taiwan
Li Qin Zhang United States
Ashley Beecham United States
Travis D. Hull United States
Elżbieta Korobowicz Poland
Faisal Ali United Kingdom
Ming Wu China
Andrea Sánchez‐Navarro Mexico
Rebecca A. Sosa United States
Dan Lan relative to Wei Guan China Wei Guan's profile →
Citations per field
00.5×4.5×
Wei Guan · 1×
Citations per year

Countries citing papers authored by Dan Lan

Since Specialization
Citations

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

Fields of papers citing papers by Dan Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009167
2 201262
3 201454
4 201642
5 201437
6 201327
7 201927
8 200925
9 201224
10 200923
11 201517
12 202115
13 202212
14 201311
15 202211
16 20169
17 20168
18 20177
19 20207
20 20157

About Dan Lan

Dan Lan is a scholar working on Molecular Biology, Genetics, Physiology, Epidemiology and Endocrinology, Diabetes and Metabolism, having authored 42 papers that have together received 640 indexed citations. Recurring topics across this work include Blood disorders and treatments (7 papers), Muscle Physiology and Disorders (7 papers), Hypothalamic control of reproductive hormones (4 papers), Neutropenia and Cancer Infections (4 papers), RNA Research and Splicing (3 papers), Erythrocyte Function and Pathophysiology (3 papers), Nitric Oxide and Endothelin Effects (3 papers) and Trauma, Hemostasis, Coagulopathy, Resuscitation (3 papers). The work is most often cited by research in Geriatrics and Gerontology (72 citations), Critical Care and Intensive Care Medicine (57 citations), Physiology (31 citations), Immunology (138 citations) and Emergency Medicine (60 citations). Dan Lan has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Liangming Liu, Karl Welte, Julia Skokowa, Guangming Yang, Yu Zhu, Yue Wu, Basant Kumar Thakur, Kshama Gupta, Martin Stanulla and Xiangyun Chen. Their work appears in journals such as Blood, Endocrine Connections, Nature Medicine, Journal of Surgical Research and The Journal of Trauma: Injury, Infection, and Critical Care.

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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